Charlotte AI Reviews

I use Charlotte AI primarily for incident response, focusing on service tickets and incident tickets.

Charlotte AI has changed the way my security team investigates and responds to threats during the response phase, as we are getting benefits from the L1 perspective. The SOC analyst does not need to conduct threat hunting or complete analysis; Charlotte AI processes this information while I provide a simple prompt to get complete visibility on the analysis, their frame, what occurred, what went wrong, where we are, what the status is, and why this particular detection has happened. We can get the narrow grid that people can use; instead of reaching multiple teams, they can access this in a single click and retrieve the logs.

Charlotte AI has helped my team reduce investigation time and repetitive manual work significantly, particularly on mean time to detection.

Regarding mean time to collection, this refers to mean time to respond. By my estimation, I would say at least 35% currently, as I have been using it for more than seven months. We are also improving from this because it is a new environment where we are deploying this, so we will go one by one because of our production environment constraints; we cannot test everything.

Charlotte AI has positively affected analyst productivity and my team's ability to handle a larger volume of security activity. It improves my productivity significantly without any negative impact. However, sometimes when I provide a prompt, the output requires slightly more refinement. It is not providing raw output where I cannot go back and check for missing pieces of information that might be lagging, particularly regarding the integration piece. I would say that in another month's time, we can improve further, as we have recently adopted this.

Charlotte AI has positively affected the experience and learning curve for less experienced members of my security team. Earlier, I communicated the challenges we faced during deployment. While deploying, we encountered issues with prompts not yielding proper outputs. We had to adjust our approach regarding the prompting, and then we could achieve better responses. The NLP is based on basic English language comprehension, whereas our team employs multiple languages, such as Hindi and English. Our technical phrases and wording differ slightly, so we have adapted accordingly. It may take some more time, but mean time to detection and mean time to respond are crucial areas where I can get complete results through consolidated outputs.

Charlotte AI's natural language capabilities are highly useful for analysts with different levels of security expertise. In the era of cybersecurity, people are focusing more on threat hunting and conducting more security analysis, and data analytics is a major component where we use NLP. CrowdStrike has had an NLP component for more than seven years. I started using it more than five years ago, which has allowed me to leverage the threat intelligence that CrowdStrike possesses.

Regarding AI's natural language capabilities, it has helped analysts, particularly security analysts with different levels of experience, in two scenarios. One is the playbook where I have created my environment-based incident response and incident ticketing that we are handling. This aspect allows me to get the playbook in a single console, providing customized dashboards. The second scenario involves the level of alerts we receive, where we have to identify whether it is a true positive or a false positive.

For example, we have a large firewall entity where certain IOCs need to be identified. Hash detections are present, and I have to correlate with my networking, my security team, and operations to find correlation. With a single click, I can create a simple prompt where I can navigate this particular IOCs to see whether it can be detected in my EDR. For that, I can consult my network team to check whether any data exfiltration has happened.

Charlotte AI helps my analysts understand and prioritize security findings based on the environment. Normally, the P1 case for one environment to another will vary. It is completely environment-friendly, but how we handle this is based on our use cases, developed from past experiences and lessons learned from other incidents and supply chain attacks. We create playbooks that guide us on any detections, so we can navigate this effectively, which helps considerably.

Charlotte AI helps with mean time to detection. I need to get the Overwatch alert or some incidents; I must verify that event, whether it is an original positive, true positive, or false positive. Instead of going back to check all the logs, I can give a simple prompt and get the output from Charlotte AI, which provides the result.

Charlotte AI has been especially valuable for particular security use cases revolving around IOCs, threat IOCs, and adversaries in the threat hunting sector. It provides 100% accurate results.

Charlotte AI could improve by focusing on language support. If it could accommodate Indian languages, it would significantly assist my team.

I have been using Charlotte AI for barely eight months because we have recently renewed our license. I have been using CrowdStrike for more than five years.

In my evaluation of CrowdStrike support, I would rate it as good; on a scale of one to ten, I can give at least an eight.

I considered a change because of dashboard limitations; I cannot install multiple agents. With a single agent, I can obtain complete end-to-end navigation of alerts, events, and incident response, enabling effective tracking of information. It provides advisory and automation features, really helping with reducing manual work. This is the one major use case I see currently. In the era of AI, we cannot afford to miss this opportunity, as AI security is crucial.

Charlotte AI fits into my team's existing CrowdStrike Falcon workflows with some initial challenges during deployment. At an earlier stage, we faced difficulties where my team was giving prompts and we could not get the expected results. After three to four months, with training provided by the CrowdStrike team, we achieved a functional workflow. It takes some time, but we manage it well because it is environment-based.

The CrowdStrike team helped me create proper and correct prompts, and now it fits well. Language is a challenge; my team members have varying levels of understanding. The NLP works behind the scenes at CrowdStrike, but the lessons learned are valuable. We probably need another two months, and we can achieve it at 100%.

My environment is both on-premise and cloud.

I use AWS, GCP, Azure, and Oracle as my cloud providers.

I have 70 to 80% confidence in the responses or recommendations that Charlotte AI provides.

To validate Charlotte AI's responses or recommendations, we rely on a large number of use cases developed in our backend SOC operations teams, where we manage the overall incidents. We have proper documentation in place to address frequently asked questions regarding specific supply chain attacks; hence, we can navigate this effectively. It helps considerably.

I would rate Charlotte AI currently at eight on a scale of 1 to 10 because of the language issues my team is facing, but I would not rate it a 10 because it is a global product that requires overall language support.

I use the capability of Charlotte AI that allows me to analyze logs most often. I give it a bunch of logs, and Charlotte AI is able to compare the logs from my network team into something that makes sense. It tells me which device is impacted by that log and which device is not, and which device I should take action on. Overall, it makes working with the network team seamless because now I don't have to second-guess what they see and what I see in my endpoints. It all checks out.

Charlotte AI has changed the way my security team investigates and responds to threats by making us faster than a speeding bullet. Instead of going through pages and pages of logs trying to figure out what is what, we can just upload it, say go look at our setup, and see what you can find out.

Charlotte AI's natural language capabilities are extremely useful for analysts with different levels of security expertise. Even if you are a beginner, you cannot go wrong in uploading the log and learning about what it says about that product. I am actually learning while using the product. Every day, I am not going to upload everything because the next time I will know, for example, I already know what this does. Let me upload something different. I keep learning as I keep using it.

Charlotte AI helps my analysts understand and prioritize security findings very much. Once we use Charlotte AI for log purposes, if we find out that a device has an outdated agent, we decide to go ahead and update that agent. If the agent is not up to date, everything else will be wonky. So we update the agent, and then the analyst is able to do the task before relying on Charlotte AI to just provide a false positive potentially.

Charlotte AI fits into my team's existing CrowdStrike Falcon workflows extremely well. It is a member of one of our teams. We count on it to do well for us.

Charlotte AI has affected analyst productivity and my team's ability to handle a large volume of security activity positively. Every time we use it, we feel a co-worker. We rely on it to give us some metrics that we couldn't otherwise get, an explanation, and a summary to our network team. That way, they understand why our response is the way it is because we now have something we can trust. We are not comparing a regular third-party Copilot or AI to tell us that. We are not uploading our data anywhere; it is all in-house.

I have 100% confidence in the responses and recommendations that Charlotte AI provides. It can see the endpoints, the agent, and everything that is going on. If we don't have confidence in that, there is nothing else we are going to have confidence in. So we have very great confidence.

I validate Charlotte AI's responses and recommendations by checking them against what I tell it to give me in the summary. I can go into a couple of endpoints to make sure that the reading is the same, that the device has been online or what it says has been online. Overall, we can compare that result. We also have other competitors, in this case, Defender, and basically, I can say, Charlotte AI says this; what about this Defender? Defender is, I see what Charlotte AI says is right. This is true; this is what we got going on.

There are particular security use cases where Charlotte AI has been especially valuable for me. Pretty much anytime we get an incident with unknown things going on or unknown traffic patterns, we rely on Charlotte AI first to get the log from our network people, to provide the information, and then we upload that log. Then we are going to get a transcription of what that says, so we can make a summary, do some more research, and then send out that nice email to our corporate people, so they know what we find, what we think is going to be happening, and what we are going to need to do to improve security in the future.

Charlotte AI has positively affected the experience and learning curve for less-experienced members of my security team. The ability to get an explanation of why a certain thing happened is invaluable because when something happens, I don't want to guess at it, especially in security. I want to know what that means, why it happened, who scanned, and whether it is a software backup or just a random scan. Is there an anomaly? Charlotte AI tells us, this has been going on. It is a periodic thing that occurs every night when there is a backup running. So that means we are no longer guessing; we are now also understanding something we didn't even know was happening every day. We are learning from it.

Charlotte AI could be improved by allowing us to upload a nice report from PowerPoint or Excel, just as other AI models do. The details they give us are so good, but right now it is all text-based, and I have to copy it and format it. I would like it to be formatted into an executive-level review or initial review, so we don't have to spend additional time formatting it. It would just be easier to present the output and what we found out without spending another hour improving how the report looks because it is not clean right now when it outputs it.

I have been using Charlotte AI about since it was released.

I assess the stability and reliability of Charlotte AI as very reliable. We could probably use more understanding of how many tokens we are using so we know how much we have remaining, ensuring we are not going crazy on it and then limiting all our token usage to one incident.

I have not experienced any downtime, crashes, or performance issues with Charlotte AI.

Charlotte AI scales with the growing needs of my organization extremely well. We are in education, and we get a lot of unusual traffic patterns from students. So, this thing is basically able to analyze, learn, and predict what is normal. I think it is a perfect companion.

I evaluate customer service and technical support as easy. We have Falcon Complete, so we just call them, and they help us out, which makes it easy to do what we need to do.

Prior to adopting Charlotte AI, I was using another solution to address similar needs. We were putting some things to Copilot. The difference is that Copilot cannot see our endpoints. So it doesn't know. It tells us what it thinks happened, but it is never 100% confident because it is just guessing. It doesn't know what that endpoint's regular pattern is. So it just tells us we think this is good, but I never know because it is based on general industry data, but it doesn't consider what is normal or abnormal for our environment.

I would describe my experience deploying Charlotte AI as easy. It is already there; it is just more about prompting really. If I prompt it correctly, it does what it needs to do, especially if my prompt and the log I am trying to parse are effective. So it does all the work for us.

I have seen a return on investment with Charlotte AI, especially when we have a limited team. Every time those logs are disproved in terms of what is an incident and what is not, it shows us that it is worth having a tool that can overlook both sides. Maybe the network team has a legitimate concern for something. We put this tool there, and it is the final judge to confirm whether this is a true incident or not because the server is fine.

The other solutions I considered before selecting Charlotte AI were minimal. I am one of the people that didn't even consider it because I knew if it doesn't integrate with everything, it is not going to be good. That is basically how it goes. Even if I use Cloud or Copilot, they cannot see what Charlotte AI can see because it can see the endpoint data. So because of that, it is an easy choice to choose whatever can see the data.

In my evaluation process comparing these options, the positive aspects that stood out are when something can see everything, it gives me faster results. I am not waiting for it to load because it can see the devices and also provide close to accurate information as possible, given I have everything up to date. The negative aspects, however, are that sometimes the reporting is not as great as I want it to be. But if that can improve, then it is all positive.

The advice I would give to other organizations considering Charlotte AI is that they need to be open-minded. They must be able to use it efficiently, input logs, and try different methods. Every organization is different, but the biggest thing is you have to be able to figure out what works for you. So I would say an organization needs to think of it as a companion rather than a threat to their job, using it to help them do their job faster and better.

What worked for us is that pretty much everything we have tried so far works well. I am not saying that we will not face challenges in the future, but right now, initially, we haven't had anything that did not work well.

I have not expanded usage yet, but I want to learn more about the credits—how we can get more and what we are going to get charged. That is the only uncertainty we have because once we know that, we can expand its use more on a daily basis without the fear of running out of credits.

I would rate this review a 9 out of 10.

I mainly use Charlotte AI as a chatbot whenever there are issues or I need help on the application. It functions as an AI help resource. When there is a problem, I ask Charlotte AI and it provides assistance.

Charlotte AI helps my analysts understand and prioritize security findings quite effectively. It saves time and serves as a guide to the right direction.

Charlotte AI significantly affects the experience and learning curve for less experienced members of my security team because many of us are new to CrowdStrike. We all struggle sometimes with the new terminology and the new application. Since we are still learning, Charlotte AI helps bridge the gap for the lack of knowledge between the technician, the application, and support.

Charlotte AI has been especially valuable in general use cases whenever there is an issue, a problem, or I need some help on the dashboard. It functions as a co-pilot. I simply ask questions and it guides me.

Charlotte AI has changed the way my security team investigates and responds to threats by shortening the time of investigation and helping me find information very quickly, especially when I provide detailed information about the issue.

Charlotte AI's natural language capabilities are useful for analysts with different levels of security expertise. I would rate it from one to ten as an eight because it is improving. I need to be specific and provide more technical details so it will give the right answer. If I am vague in my questions, it does not understand very well.

Charlotte AI fits into my team's existing CrowdStrike Falcon workflow because it is always accessible whenever I log on to the main dashboard. It is positioned on the side, and whenever I need it I simply click on it.

Charlotte AI has positively affected analyst productivity and my team's ability to handle a larger volume of security activity. It helps reduce time. Whenever I ask a question, it helps me instead of my having to find information on my own, and it guides me in the right direction. It is similar to talking to support.

Charlotte AI scales well with the growing needs of my organization. The needs that we have now are being met. Since we are new to the CrowdStrike application, there is no lag.

Charlotte AI can be improved by being more precise when questions are asked. Similar to other chatbots, it needs to collect more information. It would be very helpful if they could provide a prompt so the technician will know what question to answer and understand the structure of the question. This would help the technician know what information to provide to the chatbot so they will get a better response.

I have been using Charlotte AI for over two years.

I would assess the stability and reliability of Charlotte AI as stable so far. We do not have any issues. For reliability, we do not implement everything that Charlotte AI suggests. When there is an issue, we get the help of the AI bot to structure the question and identify the issue better. We then escalate to the human level. This way, we do not take any action based on what Charlotte AI tells us unless we verify with the appropriate support.

I have not experienced any downtime, crashes, or performance issues.

My team has expanded usage of Charlotte AI, and the process was smooth. As I learn from the questions, Charlotte AI becomes a starting point whenever there is an issue. Whenever there is an issue that I am not familiar with, I ask Charlotte AI to guide me through it.

I validate Charlotte AI's responses and recommendations by working with professional services from CrowdStrike. When we have issues, we ask Charlotte AI for help in finding and minimizing the issue, and then we draft the tickets correctly to support so they can assist us further.

I would evaluate customer service and technical support from CrowdStrike as great. We have a big contract with them, and whenever there is an issue, the responsiveness is good.

Prior to adopting Charlotte AI, I was not using another solution to address similar needs.

I would describe my experience with deploying Charlotte AI as great so far. In our case, we have professional services, so Charlotte AI serves as a bridge. Whenever I have issues, it helps me format and find the source of the issue so I can formulate the best request to open a service desk ticket.

I have seen a return on investment with Charlotte AI so far.

The data points and examples I can share indicate that the environment is more secure. There are fewer vulnerabilities than we previously had. We receive notifications whenever there is an issue, which is why we signed up for this service.

The other solutions I considered before selecting Charlotte AI included Copilot and ChatGPT, primarily because we are a Microsoft shop.

In my evaluation process when comparing these options, CrowdStrike stands out positively because it is very well known in the market. It has a trusted name, has been adopted by many big companies, and is continuously evolving. CrowdStrike is dominating the product, especially now with the partnership they have with NVIDIA and the new features they have introduced. I always go with the established leaders.

Charlotte AI has helped my team reduce investigation time. For repetitive manual work, I am not aware that my team has used it. We mainly use it to ask questions whenever I get lost in the application or need more information quickly. It has shortened the time and directs me exactly where to go.

The main challenge is the learning curve. AI chatbots are new, and the more I use them, the better they become. For now, I believe we are satisfied with what we have.

My advice to other organizations considering Charlotte AI is that it is a good consideration compared to what is available in the market. It depends on whether they are buying the Falcon products from CrowdStrike. It is a good add-on. If an organization is new to CrowdStrike, I strongly advise getting Charlotte AI to navigate through the application. I would rate my overall experience with Charlotte AI as an eight out of ten.

Charlotte AI has been especially valuable in my work at a hospital, as we have many doctors traveling and logging in from potentially suspicious countries. It is good to do some investigation on that and determine whether this is actually the user we think it is logging in from Taiwan or from Pakistan. In those use cases, I believe Charlotte AI provides the most value to us.

Charlotte AI has changed the way my security team investigates and responds to threats by providing valuable insights in quick succession, allowing us to verify what it has found and then move forward to determine whether something was malicious or benign.

Charlotte AI's natural language capabilities are fantastic for analysts with different levels of security expertise because it provides very high-level professional expertise to anyone, regardless of their total understanding of what they are reading. It provides very valuable insights.

Charlotte AI provides very detailed analysis of events, which allows me to dig deeper. It provides an initial analysis, and then I can provide more detail and context to it for a secondary analysis, and a third and a fourth if I were so inclined.

Charlotte AI helps my analyst understand and prioritize security findings by providing a focus on what actually matters, and it decreases the time required to find relevant logs and information needed for proper analysis of an event or a detection.

Charlotte AI fits very well into my team's existing CrowdStrike Falcon workflow as we have a number of CrowdStrike products, including identity and exposure management, and we have also recently added the AIDR module. I think it flows and fits into all of those very well, pulling data from each source for its analysis.

I have mixed confidence in the responses or recommendations that Charlotte AI provides because in the beginning, I was not a big fan of it. I felt that it was giving me a lot of incorrect information. However, over the past year, I feel that it has become more accurate. There is still work to be done, but I can see the potential.

I believe Charlotte AI can be improved as the frontier models improve. I would like to see the false positive rate decrease. I would also like to see its ability to determine whether something was benign get better, as it does have a tendency to be overprotective and overcautious and does not really understand when something is business as usual.

In assessing the stability and reliability of Charlotte AI, I would probably give it three and a half out of five stars, as sometimes it does sit there thinking for a very long time, and then I have to come back to it later or sign off, sign back in, and try it again.

I have been using Charlotte AI for about a year.

In terms of reliability, I would say it is pretty reliable, but in terms of its conclusions about detections or incidents, it can be a real hit or miss. However, I have seen that improve over time, so I would conclude it is only going to get better and become more reliable.

I have experienced downtime, crashes, or performance issues with Charlotte AI, but I have also seen those get better and the frequency with which it happens has decreased over time.

Charlotte AI scales very well with the growing needs of my organization. We are a very small team and having the power of AI amplifies our abilities and the ground we can cover.

I evaluate customer service and technical support as great.

What makes customer service and technical support great is that they always respond to me when I have questions, and I do have many questions. I have created many support tickets over the years.

Prior to adopting Charlotte AI, I was not using another solution to address similar needs, as Charlotte AI is my first exposure to using AI in the cybersecurity defense realm.

I would describe my experience with deploying Charlotte AI as very easy, as I do not think a whole lot was needed.

While I did not actually deploy Charlotte AI, I can say that it was straightforward.

I have seen a return on investment with Charlotte AI. Although I am not the financial decision-maker, in terms of its impact, I would say it is pretty obvious that Charlotte AI is a value to us.

Before selecting Charlotte AI, I did not consider any other solutions because when I came on board, they already had Charlotte AI.

I do not know if they evaluated any other companies, but I think they are very pro-CrowdStrike and have been for several years.

I normally use the conversation capabilities of Charlotte AI the most.

Charlotte AI has affected analyst productivity and my team's ability to handle a larger volume of security activity, especially since we are a very small team. Having this capability has been very useful for us. As I mentioned earlier, it decreases the amount of time we need to spend combing through countless logs, as it can do all of that very quickly and efficiently for us and give us a starting point or a lead.

Charlotte AI has helped my team reduce investigation time and repetitive manual work.

Charlotte AI has affected the experience or learning curve for less experienced members of my security team in a limited way because we are such a small team and we outsource to a third-party SOC for low-level detections. Anything they cannot handle, they escalate to our team, which is all senior-level people, a small group of senior-level analysts.

I validate Charlotte AI's responses and recommendations by starting with the responses by going into our SIEM, which is Splunk, looking up the logs, and also looking at the log data we have coming into NextGen SIEM and into CrowdStrike's management console. In terms of its findings, I take it with a grain of salt. Its conclusions can be good but are susceptible to being incorrect. So, it does need to be verified. However, it provides an excellent starting point to anyone looking to investigate an event.

I have not really expanded usage of Charlotte AI, as I do not think that applies to us so much.

I actually use Charlotte AI the most of anyone on the team, which may also be the reason I have the most complaints since I see the good and the bad about it. I use it on just about every type of detection that comes in. It is a conversation I have with Charlotte AI, and it really depends on what I am looking for and what I want to get out of the conversation with the AI. If I am coming into it having no idea where to start, I can approach it that way, and Charlotte AI will give me a full breakdown if I ask for it. Alternatively, I could come in with preconceived notions and already gathered evidence and just want a second opinion on something, which I could also get from Charlotte AI that way.

I advise other organizations considering Charlotte AI that it really depends on their budget, but if they can fit it in, I think it is definitely a valuable tool and will increase the power of any analyst they have. Overall, I would rate this review a 7.

I primarily use Charlotte AI for the capability that provides explanations for detections. I prefer this feature specifically because it delivers a more human-readable format versus just presenting data. I use Charlotte AI for the descriptions of detections, so outside of that, I am not that familiar with it. However, it has been especially valuable for particular security use cases.

Charlotte AI's natural language capabilities are very good for analysts with different levels of security expertise because even if they don't have technical knowledge, it reads out what happened in a simple manner. Charlotte AI fits into my team's existing CrowdStrike Falcon workflows very well; it simply appeared and we started using it. Charlotte AI seamlessly integrates when needed.

Charlotte AI helps my analysts understand and prioritize security findings by providing its own evaluation of whether it's a true positive or false positive. When it indicates a true positive, it allows them to pay more attention to it and respond faster. Charlotte AI has positively affected the experience and learning curve for less experienced members of my security team.

Regarding the responses and recommendations Charlotte AI provides, I have approximately twenty percent confidence in them. I do not trust it, but it is valuable to have. I have had situations where Charlotte AI was not accurate. In my opinion, Charlotte AI can be improved by having an input feature that asks whether it was correct, how accurate the response was, and I want CrowdStrike to release new features. What would make it a ten for me is if it were more accurate.

I have been using Charlotte AI for approximately one to two years.

I would assess the stability and reliability of Charlotte AI at approximately sixty to seventy percent for a reliability rating. It is stable and does not crash.

Charlotte AI fits in well with the growing needs of my company. I have not expanded usage and am not planning to.

I have never had to contact support for Charlotte AI, so I cannot evaluate it. The process of opening tickets for other issues is straightforward. On a scale of one to ten, I would rate the support level as a ten with no issues.

Prior to adopting Charlotte AI, I was not using another solution to address similar needs.

I believe we have the free version of Charlotte AI, so I have seen a return on my investment.

I did not select Charlotte AI; someone else made the decision regarding it. I think they selected Charlotte AI because we have a free feature. I believe it is limited and we do not have the full package.

Charlotte AI has not changed the way my security team investigates or responds to threats; it simply makes the process a little bit faster. It improves our speed by approximately ten percent. I do not believe Charlotte AI has helped my team reduce investigation time or repetitive manual work; it removes one step of writing out the narrative and makes the process a little bit faster. It improves our investigation by reducing investigation time by approximately ten minutes.

Charlotte AI has positively affected analyst productivity and my team's ability to handle a larger volume of security activity. We validate Charlotte AI responses in the same way we would validate information if it was not there, by going through the triage process we have for that specific case. It makes my investigation a little bit faster because it is correct a lot of the time. I personally do not trust it, but it is correct a lot of the time, and especially for junior analysts who do not know what they are looking at, it is easier for them. I would rate this review as a seven out of ten.

I use Charlotte AI to investigate detections and incidents to help identify if they are false positives or true positives.

Charlotte AI has helped me understand some difficult things and react faster.

Charlotte AI has improved my reaction time and the time I spend investigating for detection and response. I would estimate that we have reduced that time by approximately 30-40%. However, we don't have as many credits per month as we would need to achieve even more improvements.

Charlotte AI has affected analyst productivity and my team's ability to handle a larger volume of security activity, allowing them to spend more time on other tasks.

When I have incidents or detections, I need to produce a report at the end. Sometimes I use Charlotte AI to build the report, which has been a huge improvement and benefit. My CISO requires comprehensive reports after investigating detections and incidents.

Charlotte AI helps new members, trainees, and people in education at my company who work in the IT security section. They benefit because Charlotte AI explains what exactly happened in a readable and understandable way, so I don't need to spend as much time explaining it to them.

Charlotte AI can determine if code is malicious or not, which is valuable because I cannot know every programming language.

The natural language capabilities of Charlotte AI are good because security employees can interact with it in an easy way and benefit from the module.

When I don't know something or I am new to CrowdStrike, I have investigations where I don't understand where the parent process movement happened or what exactly caused the detection or incident, and Charlotte AI helps clarify this.

When things repeat with mostly minor information changes about detections and incidents, Charlotte AI has information about past occurrences, so I don't need to investigate them and can prioritize other detections instead.

Charlotte AI asks if I want to repeat the steps or if something needs to be changed. If I decide to go deeper and use more credits, I can change something, though most analysts use the same methods.

Charlotte AI helps my analysts understand and prioritize security findings.

Charlotte AI fits well into my existing CrowdStrike Falcon workflows.

I created specific workflows with Charlotte AI after activating it, and I use them alongside other workflows.

In the beginning, it was a little difficult because I needed to get used to Charlotte AI. The more I work with it, the more it understands my environment. At the beginning, it was not as effective, but now I am confident that Charlotte AI responds with good information, good visibility, and makes fewer mistakes.

Charlotte AI has been especially valuable by assisting in doing reports.

Charlotte AI can be improved by providing more credits. I believe Charlotte AI should be able to scan more file extensions. Currently, only two, three, or four file extensions can be scanned, and I want to upload files to the cloud and receive reports on whether they are viruses or not for a broader range of file types.

I have been using Charlotte AI for two to three months.

Before Charlotte AI, I was not using another AI to do the same sort of work.

I have not considered using any other AI agents. In a couple of months, I will have a renewal of the license, and I might keep in mind increasing the credits for Charlotte AI because it is working very well.

I rate Charlotte AI a 10 because it helps a lot. It is fast, very well trained, and offers many possibilities for improvement and enhanced performance for my environment.

My main use case for Charlotte AI is to create queries based on the syntax, and I sometimes use it to triage detections and to do reporting.

For example, I had a specific, complicated query related to some kind of detections, and it was easier for me to create a query based on Charlotte AI than spending my time with the documentation to do it on my own, so it saved me a lot of time.

I use Charlotte AI mostly to research the documentation and create queries.

I don't use Charlotte AI to help our analysts understand or prioritize security findings.

I don't use Charlotte AI for analyst productivity or handling a larger volume of security activity.

Charlotte AI has positively impacted my organization by enabling response and research within a shorter time.

Searching the documentation or creating queries is much quicker than usual.

Charlotte AI has changed the way my security team investigates or responds to threats by being used sometimes to get context from the detections.

In incident response, Charlotte AI helps reduce investigation time by asking questions, and it reduces repetitive manual work for queries or documentation.

Charlotte AI has affected the experience and learning curve for less experienced members of my security team by helping with learning. It explains everything in easy language that they want to ask.

The best features Charlotte AI offers include the creation of agents and multiple identities, which is a pretty cool use case that is straightforward. I just use the prompting and it creates agents, so it is really seamless.

Agent creation helps me day-to-day by potentially triaging detections or assisting with threat reporting based on my trainings.

Regarding Charlotte AI's AI capabilities, I think its governance and security are good.

Charlotte AI's accuracy and reliability of output are much better than a few months ago.

Charlotte AI's natural language capabilities are great. If someone is a beginner, it is much easier for them to triage detections and helps them understand more context.

Charlotte AI is a great add-on that fits well into my team's existing CrowdStrike Falcon workflows.

I have pretty big confidence in the responses from Charlotte AI, but I manually verify them sometimes to check if it is correct.

Charlotte AI is good right now, but for sure, the frontier models and to mostly see some kind of threat development probably will be useful for Charlotte AI to develop. I think developing what is there and improving how it works is important, and I think it is already integrated with most of the platforms.

I have been using Charlotte AI for about a year.

Charlotte AI is stable.

I didn't find many scalability issues along the way.

The customer support is great, although I had some problems with the vendor.

I use the free version, the demo, for my experience with pricing, setup cost, and licensing.

I didn't evaluate other options before choosing Charlotte AI because it is part of the product.

I rate Charlotte AI a seven out of ten.

I choose seven out of ten because I think the product has developed to make fewer mistakes, so I think it is a decent number.

My advice to others reading reviews on PeerSpot looking into using Charlotte AI is to go for it.