Acceldata Launches Autonomous Data & AI Platform for Agentic AI Era. Learn More →

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Every execution.
Every step.
Every signal.

Every prompt, model call, retrieval step, and tool invocation — captured, connected, and searchable.
Debug the exact request that broke.

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TRUSTED BY ENTERPRISE DATA TEAMS WORLDWIDE

Full visibility into every execution.

Six signal layers. One connected trace. No gaps.

End-to-end execution tracing

Capture the full path of every request — from intake through orchestration, retrieval, model inference, tool calls, guardrail checks, and final response — as a single connected trace.

Tool call monitoring

Log every tool invocation with name, arguments, response, status, latency, and retry behavior. Surface tool misuse and dependency failures before they reach users.

Step-by-step run debugging

Inspect any run as a step-by-step timeline. See inputs and outputs at each step instead of inferring what went wrong from aggregate dashboards.

Cross-version comparison

Compare traces across models, prompts, and versions. Validate that a change did what you intended — and didn't quietly break something else.

Token, cost, latency & error tracking

Every trace carries token usage, cost attribution, latency breakdown, and error context. Catch usage trends before they become budget conversations.

Centralized search

Search across every captured signal in one place. Move from a flagged alert directly into the relevant trace and supporting evidence in one workflow.

How it works

From instrumentation to fix in four steps

Instrument

Add lightweight SDK instrumentation or use a native framework integration. No infrastructure changes required.

pip install acceldata-sdk

Capture

Every request automatically generates a complete trace — prompts, model calls, retrieval steps, tool invocations, and outputs.

req

trace

span

log

Visualize

Traces appear as connected execution timelines with filters for project, model, prompt version, environment, and status.

Debug

Drill into any failed run, inspect each step, compare against successful runs, and ship the fix.

Error: timeout at step 3

No proprietary format. No lock-in.

Acceldata ingests traces over OpenTelemetry and OTLP — the same telemetry pipeline you already use.

OpenTelemetry and OTLP
Native OTEL ingestion — same pipeline you use today. No new agents, no new agents.

Framework integrations out of the box
LangChain, LangGraph, LlamaIndex, OpenAI, Anthropic, CrewAI, AutoGen, ADK — native or SDK.

Cross-platform ingestion 
OTLP ingestion across cloud, on-prem, and hybrid environments — no per-platform rewrites.

Built different. For production AI.

Not a dev tool retrofitted for scale. Designed from the ground up for agentic complexity at production volume.

Trace fidelity built for agentic complexity

Acceldata captures the parent-child structure of agentic execution — orchestrators, sub-agents, tool calls, retrieval steps — without flattening it into a single span.