Braintrust offers a complete package of tools for developing AI applications that can be used as part of larger enterprise solutions. This includes tools for evaluating AI models, testing and experimenting with AI models through an interactive prompt tool, and managing data needed for AI model training and evaluation. Braintrust's AI application development tools are designed to simplify and streamline how AI is developed and implemented into an organization's workflow. As such, it primarily supports businesses or organizations that develop AI-enabled products.
Founded by AI/Engineering professionals Mike Knoop and Malte Ubl in San Francisco, California.
Raised $5.1M from investors in its first round of funding to develop its enterprise-wide AI application development platform.
Cloud-based with distributed team infrastructure
Enterprise AI evaluation platform with prompt engineering, model testing, and production data management capabilities
Based on ZoomInfo tech stack data and product descriptions
| Service | Cost | Details | Source |
|---|---|---|---|
| Free | $0 | Up to 5 users, 1M trace spans/month, 10,000 scores/month, basic features for small teams and pilots | — |
| Pro | $249/month | For 5 users, increased quotas, extended data retention, additional usage billed flexibly, prorated first month | — |
| Enterprise | Custom quote | High volume data, self-hosting, hybrid deployment, dedicated support, advanced security | — |
| Feature | Braintrust | LangSmith | Helicone | Comet Opik |
|---|---|---|---|---|
| Core Functionality | AI observability, evaluations, monitoring | LangChain integration, monitoring | AI gateway, observability | ML experiment tracking + observability |
| Starting Price | $0 (Free tier) | $0 (Developer) | $0 (10k reqs/mo) | $0 (open source) |
| Free Tier | Yes (1M spans/mo) | Yes (5k traces) | Yes | Yes (open source) |
| Enterprise Features | SSO, RBAC, audit logs, hybrid | Self-hosting, advanced support | — | Self-hosting |
| API Availability | Yes (SDK, OpenTelemetry, Proxy) | Yes | Yes (proxy) | Yes |
| Support Options | Email, docs (paid priority) | Paid plans | Community + paid | Community + paid |
| Security Certifications | SOC 2 Type II, HIPAA, GDPR | |||
| Deployment Options | Cloud, hybrid, self-host (Ent) | Self-host (Ent) | Cloud/proxy | Self-host/open source |
BrainTrust has a very user-friendly interface that works well for nontechnical users of your team and offers an incredibly generous free version for small teams (one million spans vs five thousand traces) but LangSmith is far better in terms of integrating into the LangChain ecosystem and open standards. BrainTrust Pro will cost you $249 flat fee versus LangSmith’s $39 per user. BrainTrust would be best for collaborative evaluation workflows.
BrainTrust for product teams with many products; LangSmith for development teams working heavily within the LangChain ecosystem.
Helicone is focused on proxy-based observability of 100 plus models and has lower entry costs ($20/seat), BrainTrust, however, provides integrated evaluations, faster query performance (80x), and enterprise compliance. BrainTrust also offers a much more generous free version for traces.
Helicone for quickly viewing your models; BrainTrust for debugging and governing your agents in production.
Opik provides both experiment tracking and observability as an open source offering which makes it perfect for ML teams who are already using Comet, BrainTrust provides much better production monitoring, real time alerts, and SOC 2 compliance, however BrainTrust is closed source beyond the ability to host themselves through their enterprise self-hosting option.
Opik for ML experimenters; BrainTrust for product teams using AI at scale.
Phoenix provides some basic open source tracing but does not provide the same level of speed as BrainTrust, nor do they provide the same level of integrated evaluations or enterprise level functionality. BrainTrust’s 80x faster queries and Loop playground provide them with a clear advantage over Phoenix in the area of production.
Phoenix for basic free tracing; BrainTrust for scalable production observability.
Test prompt changes, model swaps, parameter tweaks against dataset before deploying
Automatically score production traffic — Asynchronous scoring and configurable sampling rates
Automatically detect quality degradation — Automated alerts and baseline comparisons
One click convert failed production cases — To permanent test cases
Individual step scoring — With recording of inter-agent message, tool call, and state changes
| Evaluation Type | Capability | Supported |
|---|---|---|
| LLM-as-Judge | Configurable LLM judges for subjective evaluation | Yes |
| Heuristic Checks | Rule-based evaluation patterns | Yes |
| Statistical Metrics | Deterministic scoring functions | Yes |
| Human Evaluation | Manual scoring and annotation | Yes |
Token usage and associated costs per trace — Per trace
Monitor and debug failures — Across all executions
Execution times, token usage, success rates — Track
Get instant alerts when quality drops — Context around which queries have been impacted
