Braintrust
Braintrust traces agent runs, scores them with evals, and surfaces production failure patterns before they ship.
Braintrust earns its keep when agents fail in ways nobody wrote a scorer for. Patterns with severity tags and Topics name the failure mode, attach evidence, and hand you a dataset row in one click, which is work LangSmith and Langfuse leave to you. The catch is commitment: $249/mo Pro plus metered data overages, and 14-day retention on free means you can't mine much history before paying.
Verified 2h ago · liveness 86/100 · cite: rightaichoice.com/tools/braintrust
- Engineering teams running multi-step or long-horizon agents in production
- AI leads who want eval-driven release gates and side-by-side prompt and model comparison
- Teams whose nested agent trace volume breaks general-purpose databases
- Platform teams tracking coding agent token spend by user, model, and branch
- Early prototypes with no production traffic — nothing to observe or score yet
- Simple single-prompt apps where basic request logging covers everything
- Teams that need open-source self-hosted tracing as a hard requirement (look at Langfuse)
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Skip Braintrust if you ship single-prompt calls with no meaningful production traffic, or if you need SAML SSO, custom retention policies, or a signed HIPAA BAA without moving to a custom-priced Enterprise contract.
Processed data is metered past the included allowance — $4/GB on Starter and $3/GB on Pro after 5 GB, which bites once your agent traffic grows.
Free Starter suits a solo engineer validating a prototype; Pro at $249/mo fits a small AI-native team shipping agents, sitting above Langfuse's open-source self-hosted option and roughly in line with LangSmith's paid tiers. Only budget for Enterprise if you need SSO, a BAA, or retention policies — custom pricing scales with volume.
In short
Braintrust — Braintrust traces agent runs, scores them with evals, and surfaces production failure patterns before they ship. Best for Engineering teams running multi-step or long-horizon agents in production, AI leads who want eval-driven release gates and side-by-side prompt and model comparison, Teams whose nested agent trace volume breaks general-purpose databases. Free to start; paid plans from $249/mo.
No head-to-head comparison for Braintrust yet — the alternatives below are the closest matches we list.
What's new in Braintrust
Checked 4 days agoAcross the latest 5 updates: 4 feature updates and 1 news mention.
Run evals 50% cheaper with workflow evals
Braintrust published a guide to cutting eval costs roughly in half by structuring evaluations as workflow evals rather than per-trace scoring.
Application logs and agent traces in one view
Application logs now appear alongside agent traces in a single view, so debugging no longer spans two dashboards.
New thread view for traces
Groups each trace turn into request, agent work, and final response, nesting sub-agent work and surfacing Debugger findings at their evidence. Public preview.
SQL charts on dashboards
Build dashboard charts from SQL queries with a visual builder editing the same query; charts inherit the dashboard timeframe, filters, and grouping. Public preview; Pro and Enterprise; data plane v2.1.1+.
Patterns severity for findings
Patterns assigns severity to findings for prioritization and filtering; your corrections with a reason are preserved in later Loop investigations. Public preview; data plane v2.18.0+.
What people actually say about Braintrust — is it worth it?
We scanned public community sources for Braintrust on Oct 15, 2026 and could not establish that the discussion we found is about this tool rather than something else sharing its name. Only 1 of the posts we fetched could be positively tied to Braintrust. Rather than publish a sentiment score built on the wrong subject, we publish nothing here and re-run the scan.
Viability Score
How well maintained and how widely used is Braintrust? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Real-time trace inspection of prompts, responses, and tool calls
- Application logs and agent traces combined in a single view (Oct 2026)
- Thread view grouping each turn into request, agent work, and response with nested sub-agent work (public preview)
- Patterns automations surfacing recurring issues with severity tags you can filter (public preview)
- Topics: automated topic classification across production traces
- Loop agent generating prompts, scorers, and datasets from a plain-language description
- One-click trace-to-dataset conversion for regression tests
- Eval scoring with LLMs, code, or human reviewers
- Quality gates that block bad releases before they ship
- SQL charts with a visual query builder on dashboards, inheriting dashboard filters and timeframe (public preview)
- Coding agent insights dashboard breaking down cost by user, API key, model, tool, and branch
- PagerDuty alerting for Loop automations and log, time-window, and environment alerts
- Task-specific custom trace views and annotation interfaces with no frontend work
- Scalable agent trace ingestion on the Brainstore database with the Nitro query engine
- MCP server for querying logs, running evals, and updating prompts from the IDE
About Braintrust
Braintrust is an agent observability platform built for teams running multi-step or long-horizon AI agents in production. Every prompt, response, and tool call is traced in real time with latency and cost attached, and as of October 2026 application logs sit in the same view as agent traces so debugging stops spanning two dashboards. Storage runs on Brainstore with the Nitro query engine, which the vendor benchmarks against competing retrieval backends for phrase counting and single-match lookup across long prompts. The evaluation side is where release discipline happens. Experiments run against versioned datasets, outputs get scored by LLMs, code, or human reviewers, and quality gates block a bad release before it ships. Discovery is the differentiator over tracing-only rivals: Patterns automations scan production traces for recurring issues and now tag each finding with a severity you can filter, Topics classifies behavior across traces at scale, and a one-click trace-to-dataset conversion turns a real failure into a regression test. Loop, the built-in agent, writes prompts, scorers, and datasets from a plain-language description. The October 2026 changelog added a thread view that groups each turn into request, agent work, and final response with sub-agent work nested underneath, SQL charts with a visual query builder on dashboards, PagerDuty alerting, and a coding agent insights dashboard breaking down cost by user, API key, model, tool, and branch. A published guide on workflow evals claims roughly half the eval cost of per-trace scoring. SDKs cover Python, TypeScript, Go, Ruby, and C#, plus an MCP server that lets a coding agent query logs, run evals, and update prompts from the IDE. Starter is free with 14-day retention; Pro is $249/mo. Against LangSmith, which leans on the LangChain framework, and Langfuse, which competes on open-source tracing, Braintrust puts its weight on automated pattern discovery and trace-scale storage.
Behind the Verdict
Where Braintrust bites is the gap between "looks fine in staging" and "quietly regressing in production." If your agents are multi-step, call tools, and spawn sub-agents, the trace volume alone will strain a general-purpose database, and this is the case where Brainstore plus Nitro pays for itself. We'd reach for it when a quality regression can't be caught by a scorer you already wrote. Patterns flags recurring issues across production traffic and assigns severity now, so you can triage by impact instead of scrolling traces. Your corrections carry a reason into later Loop investigations, which means the system gets less noisy the more you use it. That feedback loop is the part competitors haven't replicated. The Pro tier at $249/mo is a real line item for a five-person team, and the meter keeps running: 5 GB processed data included, then $3/GB, and 50k scores then $1.50 per 1,000. Run the usage calculator before you commit. For teams scoring heavily, the recent workflow-evals guidance is worth reading first, since the vendor reports roughly half the cost versus per-trace scoring. When to pass: single-prompt apps where request logging answers every question, or pre-launch prototypes with no traffic to observe. Langfuse wins on open-source tracing if self-hosting is a hard requirement; LangSmith makes more sense if you're already deep in LangChain and want the framework and the tracer from one vendor. Watch the preview labels. SQL charts, thread view, and Patterns severity are all public preview, and SQL charts need Pro or Enterprise plus data plane v2.1.1 or later. If your roadmap depends on custom charts today, confirm availability on your instance before standardizing. One practical caveat on the free tier: 14-day retention is short. You can instrument and
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Real-world workflow fit
Concrete scenarios for the personas Braintrust actually fits — and what changes day-one when you adopt it.
A customer support agent starts giving wrong refund answers. You open the thread view, follow the conversation turn by turn, see the sub-agent that misread the policy doc, and convert that trace to a dataset row with one click.
Outcome: A regression test built from the real failure is running in CI before the next release, and the quality gate blocks any prompt change that reintroduces it.
You have hundreds of production traces a day and no hypothesis about what breaks. You turn on Patterns, filter findings by severity, correct one severity with a reason, and have Loop investigate the top item.
Outcome: Loop writes a scorer and a prompt revision for the highest-severity pattern, and Topics tells you which request categories to prioritize next.
Your team's Claude Code and Cursor usage shows up as a growing line item. You open the coding agent insights dashboard and break cost down by user, model, tool, and branch.
Outcome: A daily Loop automation surfaces recurring inefficiencies, and you route budget alerts to on-call through the PagerDuty integration.
Use Cases
- Monitor production LLM traces in real time to catch drift and silent regressions.
- Convert a bug-causing trace into a dataset record for regression testing.
- Run automated evals in CI to block prompt changes that degrade quality.
- Use the Loop agent to generate better prompts, scorers, and datasets.
- Have domain experts annotate AI outputs in a task-specific review view.
- Compare two model versions side-by-side across hundreds of test cases.
- Filter Patterns findings by severity to prioritize which production issue to fix first.
- Track coding agent token spend by user, model, and branch.
Models Under the Hood
as of 2026-10-16
Limitations
- The free Starter tier includes 1 GB processed data and 10k scores per month with 14-day retention, plus $10 in model credits.
- Pro is $249/mo and raises that to 5 GB processed data, 50k scores, 30-day retention (extendable to 180 days at $0.50/GB/mo) and $100 in model credits.
- Overage is metered: $4/GB and $2.50 per 1k scores on Starter, $3/GB and $1.50 per 1k scores on Pro, with model credits billed at token rates once included credits run out.
- RBAC, custom charts, environments, and priority support are Pro-and-up; custom retention policies, S3 data export, SAML SSO, HIPAA BAA, and on-prem or hosted deployment are Enterprise-only.
- SQL charts, thread view, Patterns severity, and coding agent insights are public preview and can change before general availability, and several require data plane versions (v2.1.1+, v2.13.0+, v2.17.0+, v2.18.0+) not yet released for self-hosting.
as of 2026-10-18
Verification history
We have re-verified Braintrust 20 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 20 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Braintrust tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Starter
$0/mo
Ideal for
Solo engineer or small team instrumenting a first agent, with real traffic under about 1 GB processed data a month
What this tier adds
Free entry point: 1 GB processed data, 10k scores, 14-day retention, $10 model credits, unlimited users and projects
Pro
$249/mo
Ideal for
AI-native team of a handful of engineers shipping agents to production and wanting custom charts, environments, and RBAC
What this tier adds
Adds 5 GB processed data, 50k scores, 30-day retention, $100 credits, custom charts, environments, RBAC, and Loop plus unlimited human review scores
Enterprise
Custom
Ideal for
Teams at scale with privacy-sensitive or high-volume data that need SSO, a HIPAA BAA, or their own retention rules
What this tier adds
Adds custom allowances, custom retention policies, S3 export, SAML SSO, MFA, HIPAA BAA, uptime SLA, and on-prem or hybrid Brainstore deployment
Where the pricing makes sense
The company stage and team size where Braintrust's pricing actually pencils out — and where peers do it cheaper.
Free Starter suits a solo engineer validating a prototype; Pro at $249/mo fits a small AI-native team shipping agents, sitting above Langfuse's open-source self-hosted option and roughly in line with LangSmith's paid tiers. Only budget for Enterprise if you need SSO, a BAA, or retention policies — custom pricing scales with volume.
Setup time & first value
How long it actually takes to get something useful out of Braintrust — broken out by persona, not the marketing-page minute.
Sending your first trace takes minutes: add the Python or TypeScript SDK and log a trace with a few lines of code. The bt CLI handles instrumentation and evals if you prefer that route. Patterns, Topics, and Loop need real production traffic before they surface anything useful — plan on a few days of data before the discovery features pay off.
Switching to or from Braintrust
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From LangSmith: Braintrust is framework-agnostic, so you instrument with the native SDKs rather than the LangChain callback handler and point your existing eval datasets at Braintrust experiments.
- →From Langfuse: swap the SDK logging calls for a Braintrust SDK and recreate prompts and scorers in the Playground and Scorers tables.
- →From ad-hoc logging: send traces via the Python, TypeScript, Go, Ruby, or C# SDK, then let Patterns surface the issues your logs never grouped.
- ↗To LangSmith: replay Braintrust datasets as LangSmith experiments and re-instrument via the LangChain callback handler.
- ↗To Langfuse: export datasets and traces, then rebuild scorers as Langfuse evaluators on a self-hosted or cloud instance.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Braintrust”, and we withheld 6: 6 could not be judged, because “Braintrust” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Braintrust.
Official links
Tools that pair well with Braintrust
Common stack mates teams adopt alongside Braintrust, with the specific reason each pairing earns its keep.
Raindrop
Raindrop traces, detects, and simulates fixes for silent AI agent failures in production before they reach your users.
TruLens
TruLens traces AI agent runs with OpenTelemetry-native evals, showing where an agent fails and where you can cut cost.
Langfuse Prompt Experiments
Langfuse Prompt Experiments runs prompt tests and evals against real production traces, with versioned prompts and one-click rollback.
Alternatives to Braintrust
View all
Raindrop
Raindrop traces, detects, and simulates fixes for silent AI agent failures in production before they reach your users.
TruLens
TruLens traces AI agent runs with OpenTelemetry-native evals, showing where an agent fails and where you can cut cost.
Langfuse Prompt Experiments
Langfuse Prompt Experiments runs prompt tests and evals against real production traces, with versioned prompts and one-click rollback.
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