Retrace
Retrace records every AI agent run, forks the failing step, and replays it to prove your fix before you ship.
Seeing where an agent broke is cheap; re-running just that span and getting a "fix verified" verdict is the part nobody else ships. Enforcement adds real teeth — circuit breakers and the pre-call hold-for-approval gateway stop a runaway spend instead of describing it afterward. If your agents run multi-step tool logic in production, this is the loop you're missing; if your agent is a single chat call, you'll never open it.
Verified 5d ago · liveness 79/100 · cite: rightaichoice.com/tools/retrace
- Engineers debugging multi-step AI agent workflows in production
- Teams that need to prove a fix resolved an incident before shipping
- Agent teams capping budget, loop, and step ceilings on live runs
- CI pipelines that want agent regression gates on every PR
- No-code users experimenting with simple single-prompt chat agents
- Projects with no multi-step tool or model orchestration to replay
- Teams looking for a general-purpose log or metrics aggregator
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Skip Retrace if your agent is a single-prompt chat wrapper with no multi-step tool orchestration — you'd be paying for fork, replay, and enforcement machinery that never fires.
Going past your tier's trace count isn't covered by a published overage rate, so a busy month means an upgrade conversation rather than a metered bill.
Free ($0) and Starter ($29/mo billed annually) serve solo builders; Pro ($99/mo) is the entry point for shipped agents that need CI gates and hold-for-approval; Teams ($399/mo) is the first tier with more than one seat; Enterprise is $24,000/yr billed annually for unlimited scale. Against LangSmith-style trace browsing, Retrace asks more per seat but bundles deterministic replay and pre-call enforcement that cheaper observability tools bill as separate add-ons. Annual billing takes 2 months off, so Starter is
In short
Retrace — Retrace records every AI agent run, forks the failing step, and replays it to prove your fix before you ship. Best for Engineers debugging multi-step AI agent workflows in production, Teams that need to prove a fix resolved an incident before shipping, Agent teams capping budget, loop, and step ceilings on live runs. Free to start; paid plans from $29/mo.
What's new in Retrace
Checked 4 days agoAcross the latest 4 updates: 2 feature updates, 1 pricing change and 1 changelog entry.
Retrace 1.24.1: Enforcement & gateway hardening
Composite AND policies short-circuit on tool-pattern scope so out-of-scope calls no longer deplete token/USD/step budgets, USD budget counters update atomically with their TTL, and the gateway returns a generic 502 on unreachable providers.
Retrace 1.24.0: Onboarding & growth
A guided quickstart takes the empty dashboard from API key to first trace with copy-paste Python and TypeScript snippets, plus a one-click demo workspace, a public trending-tapes gallery, and first-party activation funnel tracking.
Retrace 1.23.0: Starter plan + pricing refresh
New Starter plan at $29/mo or $290/yr with 10,000 traces/mo, 30-day retention, 100 fork replays, 25 prove-the-fix runs, and Cassette VCR. Enterprise becomes self-serve annual at $24,000/yr; existing Pro/Teams subscribers are grandfathered.
Retrace 1.22.0: Reliability Platform + Enforcement
Pre-call enforcement adds circuit breakers, budget ceilings, loop breakers, and tool-pattern action policies that block or hold an agent action before it runs, with an SDK pre-call gate, hold-for-approval queue, and MAST failure taxonomy.
What people actually say about Retrace — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
47 mentions across 3 sources (Hacker News, GitHub, Lemmy) · researched Jul 3, 2026.
Average across the 3 sources that answered — each source counts once, not each post.
- +Fork and replay agent runs to reproduce and fix failures deterministically.
- +Step-by-step execution timeline with full state inspection at each turn.
- +Side-effect free re-runs: no external API calls during replay forks.
- +Integrates directly with LangChain, CrewAI, AutoGen, and custom SDKs.
- +Breakpoint debugging on specific tool calls or LLM turns.
- −Code changes during replay cause divergence, limiting what-if experimentation.
- −Very limited community presence, making peer support scarce.
- −No Reddit, YouTube, or Product Hunt coverage to evaluate real-world usage.
- −Notion of separate open-source project with same name causes confusion when searching online.
- −No data on performance with large-scale or high-frequency agent traces.
- • Self-hosted likely requires dedicated infrastructure and team effort to maintain
- • Freemium tier may cap number of runs or team members
Viability Score
How well maintained and how widely used is Retrace? 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
- Record every LLM call, tool call, cost, and error with one @retrace.record decorator
- Fork from any span in a recorded run and re-run the branch in a sandbox
- Prove-the-fix verdict: improved, regressed, or unchanged
- Cassette VCR deterministic replay for repeatable re-runs
- Real-time streaming of agent events onto a scrubbable timeline
- Guardrails and circuit breakers that halt a run on loops, steps, or budget ceilings
- Pre-call enforcement gateway with hold-for-approval to block bad actions before they run
- MAST failure taxonomy: auto-classification into 14 failure modes
- Detection for hallucination, groundedness gaps, drift, and failure clustering
- CI regression gates that fail the build on agent regressions
- LLM-judge evaluations, auto eval-rules, and datasets
- Multi-agent session tracing with causal graphs and agent topology
- Agent memory inspection, prompt versioning, and shareable tapes
- Semantic search: describe the bug in plain language
- OpenTelemetry ingest and one-decorator SDK for Python and TypeScript agents
About Retrace
Retrace is an execution replay engine built for engineers running multi-step AI agents in production. You install the SDK, add one @retrace.record decorator, and every LLM call, tool call, cost, and error your agent makes streams onto a scrubbable timeline. Calls to OpenAI, Anthropic, and Gemini are captured automatically, and the decorator is framework-agnostic across LangChain, CrewAI, and LlamaIndex. The core loop is record, fork & replay, fix, prove the fix. When a run fails — an OOM at step 4, a grounding gap, a loop — you fork from the exact span that broke, change the prompt, a tool input, or the model, and re-run the branch. A verify-fix verdict comes back improved, regressed, or unchanged, so you know the corrected path holds before it reaches users. Every recorded failure becomes a regression test you can re-run on each PR. Four platforms wrap that loop. Detect flags groundedness gaps, statistical drift, failure clusters, and MAST-classified failure types. Enforce halts a run at a budget, loop, or step ceiling and blocks bad actions through a pre-call gateway with hold-for-approval. Evaluate turns quality into CI gates and eval rules on datasets. Understand maps sessions, agent topology, agent memory, prompt versioning, and shareable tapes for multi-agent systems. Since the 1.23.0 changelog, pricing runs from a free tier with 1,000 traces a month up through $399/mo Teams and a $24,000/yr self-serve annual Enterprise plan. That puts Cassette VCR deterministic replay and 25 prove-the-fix runs per month in reach at $29/mo. Versus trace browsers like LangSmith, the difference is enforcement plus a proved fix rather than a prettier dashboard of what already burned your budget.
Behind the Verdict
Most agent observability tools answer "what happened." Retrace answers "did my fix work," and that is the question that actually blocks a deploy. We'd reach for it the moment an incident takes an hour to diagnose because nobody can reproduce the run — fork from the failed span, replay the branch, get a verdict. The Starter tier is the interesting one. At $29/mo or $290/yr you get Cassette VCR deterministic replay, 100 fork replays, and 25 prove-the-fix runs, which is enough for a solo builder to build the habit before committing to Pro at $99/mo. Pro adds CI regression gates and multi-agent detectors, and Teams at $399/mo brings 10 seats plus a 50,000-trace sandbox environment for testing changes off production data. Enforcement is where Retrace separates from trace-viewing rivals. The 1.24.1 changelog tightened composite AND policies so out-of-scope calls stop depleting token, USD, and step budgets — a small note with real cost implications, because a budget counter that leaks is a budget counter you can't trust. The 1.24.0 release added a guided quickstart from API key to first trace with copy-paste Python and TypeScript snippets, which cuts the usual "weekend to instrument" tax. The honest caveat: Retrace is built around individual runs, not as a log or metrics aggregator. It wants Python or TypeScript agents with real multi-step orchestration. Bolt it onto a single-prompt wrapper and you get a dashboard with one span on it. Where it bites is the workflow, not the product. If your team won't fork a run and read the divergence, the verdict has nothing to judge against — this rewards engineers who actually investigate. Teams that prefer alert thresholds and post-mortems will find the runtime enforcement a bigger behavior change than the price. Against LangSmith,
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Real-world workflow fit
Concrete scenarios for the personas Retrace actually fits — and what changes day-one when you adopt it.
A production incident-RCA agent fails at step 4 with an OOM. She opens the recorded trace, scrubs the timeline, and forks at the failed span to change the tool input before re-running the branch.
Outcome: The fork traces the real cause — a deploy that raised batch size 50× — and prove-the-fix returns a "fix verified" verdict before the patch ships.
He turns a recorded production failure into a regression test, adds the verify-fix CLI step to the pull-request pipeline, and sets a CI gate that fails the build when the judge score drops below 0.80.
Outcome: Agent regressions get caught on the PR instead of reaching users, and every merged fix leaves a permanent trace to re-run.
Loop breaker trips at 12 repeated calls. She inspects the agent topology graph, checks memory and prompt versions across the session, and sets a circuit breaker plus a hold-for-approval policy on the runaway tool pattern.
Outcome: The pre-call gateway holds the bad action before it executes, so a bug can't cascade into a cloud bill.
Use Cases
- Replay a failed agent run to identify the exact tool call that caused the error
- Fork a successful run to test a prompt variant without side effects
- Compare two runs side-by-side to understand behavior differences
- Set breakpoints on LLM calls to inspect reasoning before a tool is selected
- Monitor cost and latency across agent runs to optimize model usage
- Share a run snapshot or public tape with a teammate to debug together
- Gate CI so an agent regression fails the build instead of reaching users
- Halt a production agent at a budget, loop, or step ceiling before it cascades
Models Under the Hood
as of 2026-10-17
Limitations
- Free caps at 1,000 traces/mo with 7-day retention and 10 fork replays/mo, with no prove-the-fix runs or Cassette VCR.
- Starter ($29/mo) includes Cassette VCR but caps prove-the-fix at 25 runs/mo and lacks CI regression gates, multi-agent detectors, hold-for-approval, and sandbox environments, which require Pro or above.
- MAST classifications are metered separately (50/mo Free, 500 Starter, 5,000 Pro, 20,000 Teams, unlimited Enterprise), and sandbox retention is limited to 7 days on Pro and 30 days on Teams.
- Playback of steps recorded with OpenAI or Anthropic models server-side requires adding your own provider API key under Settings → Provider API keys.
as of 2026-10-04
Verification history
We have re-verified Retrace 10 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-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — 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 10 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 Retrace tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
Engineers evaluating Retrace on a side project or a staging agent before committing budget.
What this tier adds
Starting tier: 1,000 traces/mo, 7-day retention, 10 fork replays/mo, and 3 guardrail policies — no Cassette VCR or prove-the-fix runs.
Starter
$29/mo
Ideal for
Solo builders running one production agent who need deterministic replay but not CI gates.
What this tier adds
Adds Cassette VCR deterministic replay, 25 prove-the-fix runs/mo, 10,000 traces/mo, and 30-day retention ($290/yr if billed annually).
Pro
$99/mo
Ideal for
Shipped agents where a regression reaching users is costly and someone is on call for the pipeline.
What this tier adds
Adds unlimited fork replays, 200 prove-the-fix runs/mo, CI regression gates, multi-agent detectors, hold-for-approval, and a 5,000-trace sandbox.
Teams
$399/mo
Ideal for
Agent teams of up to 10 people who need shared traces and collaboration on the same runs.
What this tier adds
First tier with more than one seat (up to 10), 500,000 traces/mo, 365-day retention, 1,000 prove-the-fix runs/mo, and a 50,000-trace sandbox.
Enterprise
$24,000/yr billed annually
Ideal for
Organizations with unlimited trace volume and an annual procurement cycle rather than a card on file.
What this tier adds
Unlimited traces, custom retention, unlimited prove-the-fix runs and users, unlimited sandbox — sold as self-serve annual at $24,000/yr.
Where the pricing makes sense
The company stage and team size where Retrace's pricing actually pencils out — and where peers do it cheaper.
Free ($0) and Starter ($29/mo billed annually) serve solo builders; Pro ($99/mo) is the entry point for shipped agents that need CI gates and hold-for-approval; Teams ($399/mo) is the first tier with more than one seat; Enterprise is $24,000/yr billed annually for unlimited scale. Against LangSmith-style trace browsing, Retrace asks more per seat but bundles deterministic replay and pre-call enforcement that cheaper observability tools bill as separate add-ons. Annual billing takes 2 months off, so Starter is
Setup time & first value
How long it actually takes to get something useful out of Retrace — broken out by persona, not the marketing-page minute.
Solo builder: under 5 minutes from pip install retrace-sdk (or npm i retrace-sdk) to first trace — the 1.24.0 guided quickstart walks API key → install → env var → first trace with copy-paste snippets. Team wiring CI gates: plan an afternoon to add the verify-fix CLI and eval gate to your pipeline. Enterprise with self-hosted ingestion via OpenTelemetry: expect a few days for rollout and provider
Switching to or from Retrace
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From LangSmith: keep your existing traces, send the same runs through the Retrace SDK, then fork a previously-failed run to get a prove-the-fix verdict LangSmith can't return.
- →From raw OpenTelemetry pipelines: point exporter endpoints at Retrace's OTel ingest and your spans appear on the replayable timeline without a code rewrite.
- →From dashboard-only monitoring (Datadog/Grafana agent dashboards): keep the metrics, add Retrace for the runs you need to re-execute rather than just graph.
- ↗To a general observability stack: Retrace exports via OpenTelemetry ingest, so spans can be forwarded to your existing collector if you standardize on one backend.
- ↗To a framework-native trace browser: you'd lose fork-and-replay and the pre-call enforcement gateway, which have no direct equivalent in most trace-browsing tools.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Retrace”, and we withheld 6: 6 could not be judged, because “Retrace” 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 Retrace.
Official links
Featured Head-to-Head Comparisons
Retrace vs Spider Cloud
Choose Retrace if you obsess over agent run quality and need to debug/fork every step. Choose Spider Cloud if your agent's main bottleneck is getting fresh web data cheaply and at scale. For most AI developers, these tools are complementary rather than competitive.
Retrace vs Temporal Ai
If you need a robust orchestration engine to build fault-tolerant AI agents and workflows that survive crashes, Temporal is the obvious choice. If your pain point is debugging existing agent runs—replaying and forking them to find issues—Retrace is purpose-built for that. Many teams may benefit from both: use Temporal for production execution and Retrace for debugging. Choose Temporal for durability at scale; choose Retrace for deep agent debugging.
Retrace vs Voyage Ai
Voyage AI and Retrace serve completely different needs: Voyage AI provides specialized embedding models for high-accuracy retrieval in verticals like finance and law, while Retrace is an observability and debugging platform for AI agent workflows. Choose Voyage if you need better retrieval for enterprise RAG; choose Retrace if you're building complex agents and need to debug them effectively. They are not direct competitors.
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