Free trial
A free tier is advertised at 5,000 traces per month with 90-day trace retention and no credit card. No time-limited trial duration is stated.
Learn moreTuringPulse
Observability and governance for AI agents in production
Advanced API
What is TuringPulse?
TuringPulse is a pattern recognition tool. A control plane for production AI agents that combines trace-level observability, rubric-based evaluations, drift and anomaly monitoring, runtime policy enforcement and a human review queue, with SDK integration and an in-portal assistant for drafting rules.
TuringPulse is a control plane for AI agents: a web platform that watches what autonomous agents do in production, scores the quality of their output, enforces rules on their actions and routes risky decisions to a human reviewer. It is built for the teams that ship agentic systems (engineering, platform, risk and compliance) and need evidence of how those systems behave once real traffic hits them, not just benchmark scores from a notebook. Setup is deliberately light. Teams install the SDK and add a decorator, and the platform starts collecting traces. The Trace Explorer renders each agent execution as a full DAG, so an engineer can open any node (an LLM call, a tool invocation, a retriever query) and compare inputs, outputs, latency and cost. From there the workflow splits into four areas. Evaluate covers rubric-based scoring of outputs and a Metrics Explorer for building KPI queries such as latency percentiles, token usage and error rates, with root cause analysis that ties a regression back to the config change, prompt update or commit behind it. Monitor tracks those KPIs on dashboards, runs drift detection against rolling baselines and fires anomaly alerts into Slack, Teams, Telegram, email or a webhook. Govern applies declarative policy rules at runtime, including an MCP proxy that inspects every tool call, plus HIPAA and GDPR compliance packs. Coordinate adds the human layer: a priority-ranked review queue, policy triggers that decide when review is mandatory and audit history of who approved what. It fits the operational gap between an agent framework and a finished product. Frameworks such as LangGraph, CrewAI and the OpenAI Agents SDK help teams build agents; TuringPulse sits above them as the layer that records, judges and constrains live behavior. That places it closer to an observability and governance suite than to a prompt tool, and it suits regulated or high-cost environments where a bad agent decision carries real money or compliance exposure. Fluent agent teams will get the most out of it; the policy, drift and evaluation machinery assumes someone is willing to write and tune rules.
How do you use TuringPulse?
1Read the docs and confirm framework support
Check the documentation for the SDK path that matches your stack. The platform lists support for LangChain, LangGraph, LlamaIndex, CrewAI, OpenAI Agents, AutoGen, Pydantic AI, Semantic Kernel, DSPy, Mastra and plain Python or TypeScript agents.
2Book a demo to scope the rollout
Teams that want a guided tour of the four pillars, or need to discuss volume and compliance requirements, can schedule a walkthrough with the TuringPulse team.
3Install the SDK and add the decorator
Instrument your agent code with the SDK and a decorator, as described in the docs. The homepage states integration takes under five minutes and does not require changes to business logic.4Inspect your first traces
Open the Trace Explorer and step through the DAG of an execution, comparing inputs, outputs, latency and cost at each node.5Set policies, thresholds and alerts
Define declarative rules and hard or baseline thresholds, then route alerts to Slack, Teams, Telegram, email or a webhook. Use the in-portal assistant for draft rules and accept only what you want applied.6Review flagged decisions
Work the priority-ranked review queue, approving, rejecting or modifying flagged agent decisions, and track the outcomes in governance insights and audit history.
Pros and cons
Pros
- Trace Explorer gives node-level DAG inspection of LLM calls, tool invocations and retriever queries with cost and latency per stepAI
- Four pillars (evaluate, govern, monitor, coordinate) cover the full production lifecycle rather than just loggingAI
- Policy engine supports over 30 condition types and can block, flag or route actions to human review at runtimeAI
- Pre-built HIPAA and GDPR compliance packs shorten the path to audit-ready governanceAI
- Free tier of 5,000 traces per month with 90-day retention requires no credit cardAI
Cons
- Pricing beyond the free tier is not stated on the homepage, so cost at production volume needs a sales conversationAI
- Policy authoring, drift thresholds and custom rubrics put real configuration work on the customerAI
- Built-in alert routing covers Slack, Teams, Telegram, email and webhooks, but other channels need custom webhook plumbingAI
- Value depends on SDK instrumentation, so agents outside the supported Python or TypeScript stacks are a harder fitAI
- Out-of-the-box compliance packs are limited to HIPAA and GDPRAI
How much does TuringPulse cost?
Pricing
The homepage describes a free tier of 5,000 traces per month with 90-day retention and no credit card required. Paid tiers and their limits are not listed on the homepage; the pricing page and demo request are the places to get specifics.
Learn moreSupport
Support is offered through documentation and a demo request form. No help desk, community forum or SLA details appear on the homepage.
Learn moreIntegrations
Frameworks include LangChain, LangGraph, LlamaIndex, CrewAI, OpenAI Agents, AutoGen, Pydantic AI, Semantic Kernel, Google ADK, AWS Strands, Haystack, DSPy, Mastra and Vercel AI. Models cover OpenAI, Anthropic, Google GenAI, Vertex AI, Bedrock, Cohere and Mistral.
Features
Trace Explorer with full DAG visualization, rubric-based evaluations, a custom metrics query builder and root cause analysis. Governance adds a runtime policy engine, thresholds and baselines, MCP tool governance and HIPAA/GDPR packs. Monitoring covers KPI dashboards, drift detection, anomaly rules and alert channels. Human oversight runs through a review queue, policy triggers and audit history.
Frequently asked questions about TuringPulse
How much does TuringPulse cost?
The homepage describes a free tier of 5,000 traces per month with 90-day retention and no credit card required. Paid tiers and their limits are not listed on the homepage; the pricing page and demo request are the places to get specifics.Does TuringPulse offer a free trial?
A free tier is advertised at 5,000 traces per month with 90-day trace retention and no credit card. No time-limited trial duration is stated.Does TuringPulse have an API?
Yes, TuringPulse offers an API.How do you use TuringPulse?
The walkthrough on this page covers 6 steps: 1. Read the docs and confirm framework support 2. Book a demo to scope the rollout 3. Install the SDK and add the decorator 4. Inspect your first traces 5. Set policies, thresholds and alerts 6. Review flagged decisions.What platforms does TuringPulse support?
TuringPulse is available on Web App.What does TuringPulse integrate with?
Frameworks include LangChain, LangGraph, LlamaIndex, CrewAI, OpenAI Agents, AutoGen, Pydantic AI, Semantic Kernel, Google ADK, AWS Strands, Haystack, DSPy, Mastra and Vercel AI. Models cover OpenAI, Anthropic, Google GenAI, Vertex AI, Bedrock, Cohere and Mistral.
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Added10/22/2026
Platforms
Web App
Pricing
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