Captar
CaptarRuntime control
SDK v1
Runtime guardrails for OpenAI apps

Runtime control
for AI applications

Enforce spend limits, tool rules, and execution policy inside your application runtime. No proxy required, keys stay local.

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Budget Guardrails showing session spend limits

Built for the modern AI stack

TypeScript
OpenAI
Next.js
PostgreSQL

AI apps leak budget, tools, and control

Runaway AI spend

Without per-request budget enforcement, model calls can silently burn through monthly limits in hours. Captar reserves budget before execution and reconciles after.

Unsafe tool calls

Tools hitting external systems without runtime guardrails create security blind spots. Captar evaluates allowlists, blocklists, and per-session limits before any tool runs.

No local visibility

When everything runs through a proxy, you lose the thread between application state and model behavior. Captar traces spans inside your runtime so debugging stays local.

Runtime guardrails without a proxy

Captar wraps your OpenAI client, reserves budget before each request, and enforces tool guardrails inside your application. Traces are rich enough to inspect later and strong enough to turn into datasets and manual evals.

Traces

Capture retained prompts and responses inside your runtime.

Total traces
+8.3%
4,827
GMCSGCHG2
Tool Guardrails

Allowlist, blocklist, and enforce per-session tool limits before any call reaches an external system.

order.lookup
45 calls · 1 blocked
web.search
32 calls · 4 blocked
db.query
18 calls · 0 blocked
email.send
12 calls · 3 blocked
refund.process
7 calls · 2 blocked
Spend Tracking

Monitor budget reservations, actual spend, and unused reserve releases in real time.

Datasets

Export strong traces into append-only project datasets for eval prep and review.

Trace Export
Strong traces → dataset rows
File Import
CSV / JSONL batch upload
Manual Eval Run
Score dataset against rubric
Manual Curation
Tag, label, and cherry-pick rows
Snapshot Export
Fork dataset at a point in time
API Ingestion
Stream traces via REST endpoint
Regression Suite
Auto-run on every dataset change
Dedup & Filter
Remove duplicate or low-quality rows
Manual Evals

Launch reviewer runs, score rows with pass/fail, and apply weighted rubric criteria.

Your personal runtime control layer

Drop Captar into your existing OpenAI workflow. No provider key handover, no proxy gateway, no infrastructure changes.

  • Budget reservation & reconciliation
  • Tool allowlists & blocklists
  • Trace export to platform
  • Project-scoped datasets
  • Manual eval review runs
  • OpenAI-compatible wrappers

Trace Inspector

Trace IDtrc_a3k9f7x2m
Status
COMPLETED
ProviderOpenAI
Modelgpt-4.1-mini
Spend$0.098
Input Tokens842
Output Tokens318

Trace Inspector

Inspect every LLM call end-to-end: prompt, completion, tokens, cost, and latency in one view.

0ms

Proxy latency added

0%

Keys stay local

OpenAI

SDK compatible

Span-first

Trace model

Built for production AI

Session-level spend reservation means you never exceed your AI budget. Reserve, commit, and release per request.

Budget Guardrails

Track every tool call inside a session. Know which tools ran, how long they took, and whether they succeeded.

Tool Tracking

Every request produces a span-first trace with parent-child hierarchy, payloads, and violations. Export traces to datasets for evaluation.

Trace Export

Session-level spend reservation means you never exceed your AI budget. Reserve, commit, and release per request.

Budget Guardrails

Track every tool call inside a session. Know which tools ran, how long they took, and whether they succeeded.

Tool Tracking

Every request produces a span-first trace with parent-child hierarchy, payloads, and violations. Export traces to datasets for evaluation.

Trace Export

Session-level spend reservation means you never exceed your AI budget. Reserve, commit, and release per request.

Budget Guardrails

Track every tool call inside a session. Know which tools ran, how long they took, and whether they succeeded.

Tool Tracking

Every request produces a span-first trace with parent-child hierarchy, payloads, and violations. Export traces to datasets for evaluation.

Trace Export

Session-level spend reservation means you never exceed your AI budget. Reserve, commit, and release per request.

Budget Guardrails

Track every tool call inside a session. Know which tools ran, how long they took, and whether they succeeded.

Tool Tracking

Every request produces a span-first trace with parent-child hierarchy, payloads, and violations. Export traces to datasets for evaluation.

Trace Export

No proxy, no key rotation risk. Guardrails run inside your application runtime. Keys never leave your infrastructure.

Local-First

No proxy, no key rotation risk. Guardrails run inside your application runtime. Keys never leave your infrastructure.

Local-First

No proxy, no key rotation risk. Guardrails run inside your application runtime. Keys never leave your infrastructure.

Local-First

No proxy, no key rotation risk. Guardrails run inside your application runtime. Keys never leave your infrastructure.

Local-First

Frequently Asked Questions

Ship AI without surprises