Trustra builds the tools that make AI provable. Our flagship AI Flight Recorder turns the chatbot logs you already have into tamper-evident proof for regulators, clients, and boards.
Open-source reader. Your raw data never leaves your machine.
Trustra reads the logs your chatbot already writes. Nothing to install, nothing between you and your customers.
Run trustra read ./logs/*.jsonl or add Trustra as an OpenTelemetry endpoint. Formats are auto-detected. PII is redacted on your machine before anything ships.
Every interaction is hash-chained at ingestion. Risk detection flags disclosure gaps, prompt injection, and toxicity automatically.
One click produces an audit-ready report mapped to the EU AI Act, India DPDP, NIST AI RMF, and ISO 42001. Hand it to a regulator, a client, or your board.
Three ways to connect
pip install trustra, point it at your log files, and PII is redacted on your machine before anything ships. Full control, open source.
No install at all. Upload log files in the dashboard or forward them from your log store, and Trustra Cloud normalizes, redacts, and chains them on arrival.
Point your LLM calls at the Trustra gateway and every interaction is captured live as it happens, with verified provenance from the first token.
Every record is SHA-256 linked to the one before it. Go ahead, tamper with one. Click any record to edit history and watch verification catch it instantly.
Click a record to tamper with it. Click it again to restore.
Explore the capabilities below, or tell us your requirements and our experts will shape the engagement.
Audits and compliance for customer-facing AI. Tamper-evident interaction history, automated risk findings, and one-click audit reports. Reads the logs you already have.
Start free →Dashboards over your accumulated trust history: disclosure rates, finding trends, evidence scores over time. Ships with every Flight Recorder account.
Audit the vulnerabilities in your AI stack against a versioned knowledge warehouse. Ranked exposure, predicted attack paths, and findings on the same tamper-evident chain.
Explore →Behavior drift, response quality, latency and token trends for LLM apps, built on the same data your reader already collects.
Explore →Trace multi-step agent runs: tool calls, decision paths, and the exact moment an agent went off-script, all on the same evidence chain.
Explore →Enforce the limits your policy already states: input screening, output checks, agent action limits, and cost caps. Every decision to allow, block, or override lands on the same evidence chain.
Explore →Drift, performance degradation, and data quality for classical and tabular models. The audit chain, extended to pre-LLM machine learning.
Explore →Independent scoring and verification of models and assistants, culminating in the Trustra Verified badge your customers can check themselves.
Explore →Outcome-based engagements delivered by our team: multi-tool cybersecurity audits, compliance readiness assessments, governance implementation across your AI stack, and custom evidence pipelines built to your requirements.
Explore expert services →Trust does not live in one place, and it is never done once. Trustra is built to govern the full stack, from the conversation your customer sees down to the infrastructure it runs on, in a continuous loop that never stops watching.
End-user conversations, AI disclosure, consent events, and the experience your customers can verify.
Every model call through the Trustra gateway: provenance, usage, and third-party AI services on the record.
Multi-step agent runs, tool calls, and decision paths, so you can replay where an agent went off-script.
Model versions, behavior, drift and fairness signals, chained into the same tamper-evident history.
Prompts, RAG pipelines, and the AI features in your stack, governed where they are built.
Compute, network, and storage evidence: where models run, where data rests, and residency proof.
Roadmap Trustra runs on-premises and on hyperscalers today. Managed availability on the public cloud, across AWS, GCP, and Azure, is on the roadmap.
The continuous governance loop
Every interaction at every layer lands on the evidence chain as it happens.
Automated detection flags disclosure gaps, injections, toxicity, and drift, continuously.
Confirm findings, remediate, and sign off, with every action joining the record.
Audit-ready reports on demand, from evidence nobody could have rewritten.
Baselines tighten and policies sharpen from what was learned, then the loop begins again.
↻ improve feeds record: governance is a loop, not an annual checkbox
One evidence chain spans all layers, so an auditor can follow a single conversation from the customer’s screen down to the model version and the region it ran in.
Whether you arrive with a use case or a regulation, the path ends the same way: provable AI. Every solution can be self-serve or delivered end to end by our experts.
By use case
Your users ask if they can trust your AI assistant. Give them verifiable answers: disclosure evidence, integrity-checked history, and a report you can share.
See how it works →Selling AI features to enterprises means questionnaires about AI risk. Answer with evidence exports instead of essays, and shorten procurement cycles.
See the deliverable →When an auditor or regulator asks what your AI did last quarter, produce the tamper-evident record in one click instead of weeks of log archaeology.
See tamper evidence →Something went wrong in a conversation. Replay exactly what happened, when, and with which model version, on a record nobody could have quietly edited.
See the chain →Prompts and chat logs are full of personal data. Redact at the source, minimize what is stored, and turn logging from liability into evidence.
See how it works →Watch behavior, quality, and risk signals over time as your trust history accumulates, with full observability with engagements shaped around your stack.
Explore the platform →A policy document blocks nothing. Screen inputs for injection, check outputs for grounding and toxicity, and record every allow and block as it happens.
See Guardrails →Token quotas, context caps, and retry limits per team or tenant, so a runaway agent cannot exhaust your budget or your capacity overnight.
See cost controls →Allowlist the tools an agent may call, bound its blast radius, require confirmation before irreversible actions, and keep a kill switch that is actually tested.
See agent controls →Measure accuracy, hallucination, and prompt injection resistance on real tasks, then turn each result into a sealed artifact your reviewers can check.
See evaluation →For auditors facing India's new DPDP engagements: a repeatable, evidence-driven workflow that replaces spreadsheets and produces defensible working papers.
See DPDP →Turn accumulated trust history into a standing view of disclosure rates, findings, drift, and spend, so governance reporting stops being a manual exercise.
See analytics →Your org runs AI in chatbots, copilots, RAG pipelines, and agent workflows. Get one tamper-evident audit across every tool, not six separate questionnaires.
Start an engagement →By regulation and standard
Map your trust history to the frameworks enterprises ask about.
Learn more →Live dashboards for your team to run on day to day, and verifiable artifacts you can hand to an auditor, a customer, or your board.
Generated from 1,849 real-format interactions across 30 days. No email gate.
No subscriptions, no seats, no platform fee. Buy credits online, spend them only when Trustra delivers: a report, a verification, a confirmed catch. Every feature is unlocked for everyone, and one credit is one dollar.
Written for builders, not lawyers. Each guide maps the evidence you need to what the Flight Recorder produces.
Users must know they are talking to AI, and AI content must be labeled. Applies to virtually every customer-facing chatbot serving the EU. High-risk obligations follow from December 2027.
India’s first comprehensive data protection regime is law, with phased enforcement underway and penalties up to Rs 250 crore. Chatbots, prompt logs, and vector stores are squarely in scope. Trustra redacts PII at your source and turns prompt logs into compliant evidence, with INR billing and UPI checkout.
The frameworks your enterprise clients ask about in security reviews. Map your trust history to both, and answer questionnaires from the self-serve trust center without a single call.
Trustra is the Trust and Responsible AI OS: one operating layer of tamper-evident records, automated risk detection, and audit-ready proof for every AI system in production.
Our mission
Make every AI system worthy of human trust.
Our vision
A world where AI judges fairly, transparent to all and trusted by all.
Our purpose
Help responsible AI make the world better, so every leader can stand behind their AI without fear.
Trustra was founded on the premise that the companies building AI deserve a way to show their work, and the people relying on AI deserve more than promises. We hold ourselves to the standard we sell: everything we claim about an AI system should be verifiable by the person asking. That conviction shapes our product, our pricing, and the way we treat every customer.
“Anyone can promise their AI behaves. We exist so you can prove it.”
Thomas Vengal is the Founder of Trustra.ai. He started the company on a simple conviction: AI adoption is stalling on one question, can anyone prove these systems behave, and answering it should take a click, not weeks of log archaeology. Thomas leads Trustra’s product strategy and engineering, building the trust platform that helps teams prove their AI is responsible to customers, auditors, and boards.
Connect on LinkedInEleven questions, under three minutes. Tell us which regulations bite, where your logs live, and which capabilities matter most to your team. Your answers shape where Trustra invests next, so the platform keeps growing where our customers need it.
Structured guides for CIOs and audit teams, with diagrams, control catalogs, and checklists you can use directly.
Ethics, Responsible AI, governance and compliance are not the same thing. A layered model, who owns each, and where programs stall.
Definitions, the seven control domains, the lifecycle model, framework mapping across the EU AI Act, NIST AI RMF, ISO 42001 and DPDP, and a phased 90-day implementation checklist.
Four guardrail layers built from the evidence foundation upward, a 34-control catalog with owners and evidence artifacts, failure modes, and an audit test plan.
Notes on AI governance, observability, and the practical work of proving your AI to regulators, customers, and boards.
Trustra gives enterprises the fastest, most robust way to scale AI governance and observability across on-premises and hyperscaler environments. Pick a time and a solution expert will walk you through it.
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