From a rapid governance snapshot to a full enterprise governance programme — start a conversation and we'll scope the right assessment for your environment.
One workspace covers workloads, tools, and environments within a single organisation. Supports Python-based workloads with auto-instrumentation for LangChain, CrewAI, AutoGen, LlamaIndex, and Haystack. Multiple organisations require separate workspaces.
Automated governance report
For teams beginning their AI workload governance journey, or organisations that want to understand their workload's behaviour before committing to a full assessment.
What's included
What it is not
Analyst-signed assurance report
For organisations deploying AI workloads in production who need a governance-ready output they can present to a risk board, auditor, or regulator.
Behavioural Analysis
Control Gap Analysis
Ongoing governance engagement
For organisations with multiple workload deployments, regulated industry requirements, or multi-client environments needing consolidated governance.
Everything in Governance Assurance Report, plus
Every AuthBinder governance assessment covers six critical dimensions. Together, they give you a complete picture of your AI workload governance posture — and the evidence you need to prove accountability.
We verify that every workload action can be attributed back to a specific identity, so you always know which workload acted and when.
We assess whether each tool call and action was within the workload's authorised scope — identifying unapproved actions and authority boundary violations.
Every recorded action is hash-chained the moment it's written and periodically signed, so any alteration of the audit history is detectable. Records are held under a 6-month minimum retention enforced at the database layer, and log integrity can be verified on demand.
Customers and their auditors can verify the integrity of the full event history on demand — a live check that recomputes the hash chain and confirms nothing has been altered or removed.
We map your workload's behavioural patterns across the full observation window — identifying anomalies, high-frequency actions, and governance control gaps.
We assess which third-party APIs and external destinations your workload accessed — mapping spend risk, data movement patterns, and unapproved service usage.
We map every point where authority enforcement is absent, insufficient, or bypassable — delivering a prioritised remediation roadmap aligned to your obligations.
Tool calls executed without human authorisation — workloads acting beyond their delegated scope
Workloads reading from protected sources and writing to unintended external destinations — governance gaps in data handling
Unusual tool call patterns, timing irregularities, and sequences flagged across 50 risk rules and 7 governance categories
Uncapped tool usage and spend loops — high-frequency calls to paid APIs causing financial and operational impact at scale
No enforcement at execution time — workloads operating beyond their delegated scope undetected across sessions and tools
Everything you need to know about AI workload governance and how AuthBinder works.
AI workload governance doesn't sit in one function. It spans security, technology, finance, compliance, and legal. AuthBinder is designed for every leader who needs answers — and evidence.
You're now accountable for AI governance, not just security. AuthBinder gives you the controls and evidence you need to satisfy the board, the auditors, and the regulators.
Understand the execution risk profile of every workload in your stack. Identify where authority controls need to be built in — not bolted on.
Quantify AI workload risk in terms your risk frameworks already understand. Map control gaps to regulatory obligations and risk appetite thresholds.
AI workload failures are already costing large enterprises over $1M per incident. AuthBinder provides the oversight infrastructure to detect scope violations before they become financial events.
AuthBinder maps directly to NIST AI RMF, EU AI Act documentation requirements, and ISO/IEC 42001. It gives you the audit evidence your frameworks require.
When an AI workload is involved in a dispute or regulatory enquiry, AuthBinder provides the forensic audit trail that establishes what happened, when, and with whose authority.
AuthBinder gives organisations the identity, authority records, and audit trails they need to govern their AI workloads — so when a regulator, auditor, or board asks what your workloads did and who authorised it, you have the answer.
Verifiable identity. Scoped authority. Tamper-evident audit trails. Built for the EU AI Act and beyond.
AuthBinder was designed from the ground up for autonomous AI systems — not adapted from legacy security tooling. We understand workload architectures, tool-use patterns, and the governance challenges they create.
AuthBinder operates entirely on metadata and telemetry — workload IDs, tool names, timestamps, destinations, and action types. No prompt text, no payload bodies, no customer records are stored. This is a core differentiator and trust signal.
We have no stake in the AI platforms or workloads we assess. Our findings are unbiased, vendor-neutral, and calibrated to real-world AI workload governance risk — not vendor marketing.
Our governance framework maps directly to emerging requirements including the EU AI Act, NIST AI RMF, NIST workload identity standards, and ISO/IEC 42001 — giving you findings that translate directly into regulatory evidence.
Every action is logged in a tamper-evident, forensic-quality trail. The Governance Assurance Report is signed analyst output — suitable for board, audit, and compliance use.
Every finding comes with a prioritised, practical remediation recommendation. We don't hand you a list of problems — we give you a roadmap to fix them.
Start a conversation and we'll scope the right governance assessment for your environment.