Sold by: Braintrust
Deployed on AWS
Braintrust is the AI observability platform. By connecting evals and observability in one workflow, Braintrust gives builders the visibility to understand how AI behaves in production and the tools to improve it.
Teams at Lovable, Notion, Stripe, Zapier, Vercel, and Ramp use Braintrust to compare models, test prompts, and catch regressions-turning production data into better AI with every release.
4.3
Overview
Braintrust is the agent observability platform. By actively applying intelligence to agent traces and automatically surfacing the most critical patterns, Braintrust gives teams the visibility to understand how agents behave in production and the tools to improve them.
Teams at Notion, Stripe, Box, OpenAI, and Cloudflare use Braintrust to trace their agents, find the issues in their observability data, and run evals that tell them how to improve.
Braintrust provides:- Data + Instrumentation: turning traces and outputs into structured eval datasets.
- Active observability: autonomous and continuous intelligence on top of your observability data, surfacing the patterns that matter.
- Evals: defining what "good" means, measure against it, and determine how to improve your agents.
- Iteration: comparing prompts, models, and versions to improve quality, cost-effectively.
- Quality gates: automated checks that prevent regressions from reaching production
- Improvement loop: AI-powered tools that speed up the entire development cycle.
Highlights
- Loop: A specialized agent for querying observability and trace data. Ask follow-up questions in plain language and get answers backed by your production data.
- Brainstore: Braintrust's database for agent observability. Search and filter millions of traces in under a second, including full-text search across prompts and error messages.
- Scalable architecture with enterprise-grade security: Braintrust is RBAC, SSO, SAML, HIPAA and SOC II compliant and offers a hybrid deployment model for customers with certain data requirements.
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Deployed on AWS
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Pricing
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
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Dimension | Description | Cost/12 months |
|---|---|---|
Enterprise SaaS License | Contact Us For Private Offer Pricing at info@braintrust.dev. | $250,000.00 |
Dimension | Description | Cost/unit |
|---|---|---|
Usage | Usage-based credits for data volume, scores, data retention, and topics | $0.01 |
Dimensions summary
Braintrust offers two separate pricing dimensions. The Usage (Units) dimension bills by consumption, charging credits for data volume, scores, data retention, and topics. Your cost rises as your processed data, scored outputs, and stored data grow. The Enterprise SaaS License (Units) dimension is a private offer negotiated directly with the vendor at info@braintrust.dev. Choose usage-based billing when you want to pay for what you consume. Choose the enterprise license when you need a custom contract, which can include tailored data retention, export, and deployment terms. The two dimensions represent distinct purchasing paths, not stacked tiers.
Top-of-mind questions for buyers
The Usage dimension meters four things: processed data volume in gigabytes, scored outputs (scores), data retention duration, and topics. Each metric bills independently and appears together. Processed data usually drives cost for high-traffic apps. Scores grow with how often you evaluate traffic. Retention adds charges the longer you store data.
A score is a scored output from an LLM-as-a-judge, an automated evaluator, or your own custom code scorer. Each scored trace produces scores that count toward your usage. Human review scores that your team fills in manually when reviewing traces are configured separately.
Usage-based billing charges credits as you consume data volume, scores, retention, and topics, so cost tracks actual activity. The Enterprise SaaS License is a private offer negotiated with the vendor. It can include custom data retention, export terms, and on-premises or hosted deployment. Contact info@braintrust.dev for that pricing.
www.braintrust.dev
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Support
Vendor support
Email us at info@braintrust.dev .
Join us on Discord!
https://www.braintrust.dev/contact
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AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Customer reviews
Irfaana H.
Streamlined AI Evaluation, Steep Learning Curve
Reviewed on Sep 10, 2026
Review provided by G2
What do you like best about the product?
I mainly use Braintrust to test and evaluate AI outputs, which helps me get a clearer picture of how different prompts and models are performing. What I like most is how much easier it makes the process of testing and improving AI outputs. I appreciate the evaluation and comparison features the most; I can test different versions of a prompt and see results side by side, easily spotting small differences in accuracy and consistency. The logging and tracing are also useful, allowing me to dig into what happened when an output doesn't come back as expected. It's helpful to see the history of my tests, especially when making several changes and wanting to understand which adjustment improved the result. Everything feels more structured with Braintrust, enabling me to quickly spot where a prompt is working well or needs adjustment, rather than relying solely on my judgment.
What do you dislike about the product?
The initial learning curve with Braintrust is a bit of a challenge. There are quite a few features, and when I first started using it, I wasn't always sure where to go or which evaluation option would be the most useful for what I was trying to test. For example, I spent more time than expected figuring out how to interpret evaluation data and understand which version was performing better. A simple guided explanation or visual summary highlighting key differences would have made the process quicker. It took me a while to get comfortable with how the different evaluation options fit together, and understanding which metrics were most important took some experimentation.
What problems is the product solving and how is that benefiting you?
Braintrust takes the guesswork out of evaluating AI outputs by providing a structured way to compare results and spot inconsistencies. I can test and evaluate different prompts, which helps improve AI outputs by highlighting where adjustments are needed.
Abdullah S.
Flexible Work with a Wide Variety of Projects on Brain Trust
Reviewed on Sep 02, 2026
Review provided by G2
What do you like best about the product?
One of the best things about Brain Trust is the wide variety of opportunities available. People with different skills and levels of experience can find projects that fit their background, which is helpful because it gives professionals more options instead of relying only on traditional job websites. This is especially valuable for those who want more flexibility in where and how they work. Overall, I really appreciate the flexibility, the range of projects, and the platform’s focus on connecting skilled professionals with companies.
What do you dislike about the product?
One thing I dislike about Braintrust is that certain parts of the platform can be hard to figure out the first time you use them. It offers a lot of useful features, but it can take time to learn where everything is and how each tool works. A simpler layout and clearer guidance would make the experience much easier for new users. I also think the search and filtering options could be improved, especially when there are a lot of projects or opportunities to sort through.
What problems is the product solving and how is that benefiting you?
Braintrust also helps teams monitor and improve AI performance. Rather than checking everything manually, they can rely on data and feedback to spot issues sooner. This saves time and makes it easier to pinpoint what needs improvement. It’s especially useful when an AI application is used by many people or has to handle a large volume of information. Braintrust also helps address several challenges that can make data, AI, and development work harder. A common problem is that teams often have to juggle different tools and systems to manage their work, and Braintrust helps bring more of that process together in one place.
Abdul R.
Braintrust’s Low-Fee Model and Expanding AI Recruiting & Automation Suite
Reviewed on Sep 02, 2026
Review provided by G2
What do you like best about the product?
I don't have personal like or preference but if I were evaluating Braintrust as a platform, the aspect I'd consider strongest is. Braintrust's original differentiator was eliminating the large commission common on traditional staffing platforms, allowing freelancers to retain 100% of their earnings while charging clients a comparatively low platform fee. Braintrust has expanded into AI recruiting, Braintrust AIR workflow automation nexus, and AI training work.
What do you dislike about the product?
I don't have personal like or dislike but some potential drawbacks are. It can take time to understand evaluations, experiments, datasets, scores, and tracing. For a small project, adopting a full evaluation framework may feel like more infrastructure than you need. As usage and evaluation volume grow, platform costs can become a factor. Very specialized evaluation workflows may require more work than simpler in-house scripts.
What problems is the product solving and how is that benefiting you?
It is solving a core problem by helping companies find and hire high-quality specialized talent faster while giving skilled professionals better access to work without traditional recruiting middlemen. Hiring specialized talent, especially in AI, software design, and other technical areas, can be slow, expensive, and difficult to verify. Freelancers and independent professionals often lose money to agencies and platforms that take significant fees while also struggling to find high-quality opportunities.
Kabir S.
Elevated AI Testing and Monitoring
Reviewed on Sep 02, 2026
Review provided by G2
What do you like best about the product?
I mainly use Braintrust for evaluating and monitoring AI applications. I find it especially helpful for keeping track of quality as we make changes. What I like most is the evaluation and comparison side of it. Being able to run the same test set against different prompts or models and see the results side by side is really useful. It makes it much easier to tell which changes are actually improving the AI instead of just guessing. The initial setup was fairly easy for our team. Getting the basic evaluation running didn't take too long, and once configured, it was pretty straightforward to use. I also appreciate how Braintrust fits naturally into our existing development and testing process.
What do you dislike about the product?
The main thing I'd improve is the learning curve around setting up more detailed evaluations. Once you understand the workflow it makes sense, but some of the configuration can feel a little overwhelming at first. I'd also like more straightforward reporting and dashboards for quickly seeing trends across multiple evaluations.
What problems is the product solving and how is that benefiting you?
I use Braintrust for evaluating AI applications, solving the challenge of measuring AI quality. It helps us test, compare, and catch issues early, making testing manageable and ensuring changes truly improve our AI.
Information Technology and Services
The Feedback Loop Our AI Team Was Missing
Reviewed on Sep 01, 2026
Review provided by G2
What do you like best about the product?
The trace UI, evaluation workflow, playground, and the ability to compare model behavior before shipping a change
What do you dislike about the product?
It's reactive, not preventive
It scores output quality after the fact, it doesn't stop a bad answer from reaching a user in real time. If you need runtime guardrails, you have to pair it with a separate tool.
It scores output quality after the fact, it doesn't stop a bad answer from reaching a user in real time. If you need runtime guardrails, you have to pair it with a separate tool.
What problems is the product solving and how is that benefiting you?
LLM output quality is hard to measure and easy to break silently
Traditional software has deterministic tests. AI outputs are probabilistic, change a prompt, swap a model, or tweak retrieval, and quality can improve or quietly regress with no clear signal. Braintrust exists to make that visible.
Traditional software has deterministic tests. AI outputs are probabilistic, change a prompt, swap a model, or tweak retrieval, and quality can improve or quietly regress with no clear signal. Braintrust exists to make that visible.