Stop your AI from making
irreversible mistakes.
Block unsafe decisions before they execute. Enforce policies at the point of action. Prove compliance with tamper-proof audit trails — ready for any regulator.
Three ways AI goes wrong in production
These aren't edge cases. They're what happens when AI systems run without a control layer.
AI approved a $50K transfer
A support agent called transfer_money with no amount limit. Nobody checked if it was authorised.
Chatbot leaked customer PII
A prompt injection tricked the model into returning email addresses and phone numbers in a response.
Agent loop burned $4K overnight
A recursive tool call chain ran 2,000 iterations before anyone noticed. The bill arrived the next morning.
"We're building an AI co-founder that mentors thousands of aspiring founders. DriftGard gives us confidence that our AI stays within safe boundaries — no bad financial advice, no harmful guidance, full audit trail. Integrated in under a day."— Joe, Founder · 7Ronin AI
Understand it in 10 seconds
What DriftGard actually does
Real-time control, continuous monitoring, and compliance proof — in one layer.
Control
Block unsafe decisions before they execute. Validate tool calls at the parameter level. Enforce identity rules. Stop agent loops. Real-time, deterministic, sub-10ms.
Observe
Monitor AI behaviour across every project. Detect drift after model updates. Track decision chains across agents. Alert on cost spikes and anomalies.
Prove
Generate compliance reports mapped to EU AI Act, NIST, ISO 42001, GDPR, FINMA, SOC 2, APRA CPS 230, and HIPAA. Tamper-evident records. Signed evidence downloads. Auditor portal. Prove governance was in place.
Customer support AI in fintech
Without DriftGard
With DriftGard
The risk moved. Your governance should too.
Most tools were built for chatbots — they check what AI says. But agents send emails, make payments, and call APIs. The risk moved from what AI says to what AI does.
What most tools do
Monitor AI responses after the fact.
What DriftGard does
Control AI decisions and actions before they execute.
Built for the people who carry the risk
Different roles, same question: "Can we prove our AI is under control?"
Chief Compliance Officer
Scheduled reports mapped to EU AI Act, ISO 42001, NIST AI RMF. Evidence vault with signed downloads. Read-only auditor portal. Regulatory deadline tracking. Stop preparing for audits — the evidence generates itself.
Head of Risk
Real-time visibility into what AI is doing across every project. Drift detection catches behaviour changes after model updates. Cost alerts stop runaway agents. Tamper-evident logs prove nothing was modified after the fact.
CTO / Engineering Lead
Two API calls to integrate. SDKs for Node.js and Python. Governance-as-code CLI for CI/CD. Zero-trust tool validation with identity rules. Circuit breaker and fail-safe modes. Ship AI features without building a compliance layer from scratch.
Security tools stop threats.
DriftGard proves you stopped them.
Open-source toolkits like Microsoft's Agent Governance are powerful enforcement libraries — and that's exactly what they should be. DriftGard is what you deploy alongside them when you need to prove to a regulator what happened and why. When regulators ask for proof, enforcement logs aren't enough.
🏛️ Compliance operations — not just enforcement
Enforcement libraries don't store tamper-evident records, generate compliance reports, or give your auditor a portal. Those aren't engineering problems — they're operations problems.
Enforcement is table stakes. Provable compliance is the moat.
| Capability | Open-source | Runtime security | DriftGard |
|---|---|---|---|
| Policy enforcement | ✓ | ✓ | ✓ |
| Tool call validation | ✓ | ✓ | ✓ |
| Per-tool identity rules | — | Partial | ✓ |
| Jurisdiction-scoped rules | — | — | ✓ |
| Local evaluation (zero data egress) | — | — | ✓ |
| Tamper-evident audit trail | — | — | ✓ |
| Compliance reports (PDF) | — | — | ✓ |
| Auditor portal | — | — | ✓ |
| Scheduled evidence generation | — | — | ✓ |
| Drift detection + alerting | — | Partial | ✓ |
| Governance-as-code CLI | — | — | ✓ |
| Time to audit evidence | weeks | weeks | minutes |
Open-source = Microsoft Agent Governance, NeMo Guardrails, etc. Runtime security = Capsule, Lakera, Operant, etc.
Aligned with OWASP Top 10 for Agentic AI
Direct mitigation for the majority of the OWASP agentic AI risks through runtime enforcement and compliance operations.
Zero-trust allowlist. Parameter validation. DLP scan on tool arguments.
Per-tool identity rules enforce which roles, agents, and users can call each function.
Chain depth limits, cost alerts, circuit breaker, and sequence ordering.
Runtime enforcement blocks violations. Drift detection catches behaviour changes.
Adversarial input detection and meta-bypass pattern matching.
Session chain tracking with parent links, sequence ordering, and integrity hashing.
Complementary coverage for ASI04 (supply chain), ASI05 (code execution), ASI06 (memory poisoning), ASI09 (trust exploitation).
The ROI case for AI governance
DriftGard isn't a cost centre. It pays for itself in one prevented incident.
200 hours → 2 minutes
Audit prep that took weeks now generates in seconds. Read-only auditor portal means zero engineering support needed.
Governance that never causes an outage
Circuit breaker with fail-open mode. If DriftGard is unreachable, your app keeps running. Governance is never a single point of failure.
The regulatory fast-pass
Ship AI features months ahead because governance is built-in, not a blocker. Compliance layer already built — tamper-evident logging, risk scoring, evidence generation.
The production enforcement layer for AI agents
Runtime policy enforcement, local zero-egress evaluation, deep tool control, and enterprise compliance evidence — model-agnostic, framework-agnostic.
Runtime Enforcement
Block policy violations before they reach users. Sync, async, or hybrid mode. Response sanitization — redact sensitive patterns while allowing the response through. Risk scoring with per-rule semantic thresholds.
Zero-Trust Tool Control
Every unlisted tool is blocked. Parameter-level rules: type, min/max, regex, enum, custom expressions. Per-tool identity enforcement (role, agent, user). DLP scans arguments for PII and secrets before execution.
Decision Chain Tracking
Session IDs, parent evaluation links, and sequence numbers reconstruct the full decision chain across multi-step agents. Chain depth limits prevent infinite loops. Out-of-order detection catches race conditions.
Local Zero-Egress Evaluation
Evaluate locally via WASM — no prompt or response data leaves your environment. Optional ONNX semantic matching (~22MB model) for paraphrase detection without external calls. Perfect for healthcare, mental health, and sovereign deployments.
Framework Integrations
Drop-in support for LangChain, CrewAI, and Strands agents. One-line guardrail in any chain. Tool guard decorators for agentic workflows. Works with any LLM provider — OpenAI, Anthropic, Bedrock, Gemini, local models.
Canary & Shadow Deployment
Test new control pack versions in production without enforcing. Shadow evaluation runs alongside your active policy — compare block rates, false positives, and impact before promoting. Zero-risk policy changes.
Policy Lifecycle Management
Versioned control packs with diff, promote, test suite, and backtesting. 8 industry-specific templates. Generate policy drafts from documents. Per-rule semantic threshold tuning. Compliance mapping to regulations (EU AI Act, AHPRA, APRA, HIPAA).
Continuous Drift Detection
Baseline vs current comparison across violation rates, severity changes, and block rates. Statistical anomaly detection catches subtle drift after model updates. False positive management with rule effectiveness scoring and auto-recommendations.
Tamper-Proof Audit & Compliance
Every decision recorded in a WORM-compliant immutable log. Hourly Merkle roots with KMS-signed external anchoring — independently verifiable without DriftGard access. PDF reports mapped to EU AI Act, ISO 42001, NIST AI RMF. Push signed roots to your own S3 bucket or webhook.
Testing & Reliability
Synthetic test generation. Benchmark suites for standardised evaluation. A/B experiments across models comparing violation rate, risk score, cost, and token usage. Backtesting against new policy versions before activation. Aho-Corasick compiled pattern matching for sub-millisecond evaluation. Bias/fairness testing across 6 demographic dimensions with disparate impact scoring.
Not just chatbots.
Multi-step autonomous workflows.
Modern AI agents make chains of decisions — tool calls, API requests, database writes. DriftGard tracks the entire decision surface and enforces identity rules at every step.
Agent Identity
Per-tool role, agent, and user rules.
Chain Tracking
Full session timeline with sequence ordering.
Cost Alerts
Stop runaway loops in real-time.
Pre-built AI safety policies
Activate in minutes. Customise with a config file. Deploy to production via CI/CD.
Financial Services
Advice boundaries, disclosure, AML/KYC. ASIC & APRA mapped.
Health AU
Clinical boundaries, medication, mental health escalation. TGA mapped. Local evaluation mode for zero data egress.
Clinical Safety
No diagnoses, no prescriptions, crisis escalation, scope boundaries. Local evaluation — no patient data leaves your environment.
Insurance AU
Claims, underwriting, vulnerable customers. ASIC/APRA mapped.
Education AU
Academic integrity, student welfare, grade boundaries. TEQSA mapped.
Wagering AU
30 rules: underage, loss chasing, self-exclusion, harm minimisation.
Telecom AU
Plan advice, billing, cancellation, vulnerable customers. ACMA mapped.
Public Sector
Citizen services, policy interpretation, privacy, transparency.
General Purpose
Baseline guardrails: content safety, PII, prompt injection.
SDK-first.
Developer-friendly.
One npm install or pip install. No 6-week consulting engagement. Industry templates activate in minutes.
Security by design
DriftGard operates independently of AI model providers. We generate tamper-evident, independently verifiable records that auditors and regulators can trust.
DLP Scanner
10+ PII types, 25+ secret patterns, 15+ adversarial patterns. Scans prompts, responses, and tool call parameters independently of evaluation.
Tamper-Evident Records
Every decision hashed at write time. Hourly Merkle roots. On-demand verification proves records haven't been changed after creation.
Access & Resilience
Multi-tenant isolation. Role-based access. SDK circuit breaker. Configurable retention periods. Australian-hosted options available.
Local Evaluation
Evaluate inside your trust boundary via compiled WebAssembly. No prompt, response, or conversation content leaves your environment. For mental health, clinical, and sovereign deployments.
Works with OpenAI · Anthropic · AWS Bedrock · Azure · Cohere · Mistral · any custom model
Simple, transparent tiers
Start with a pilot audit. Scale into runtime governance as your AI rollout grows.
- All compliance features included
- Drift monitoring and alerts
- Backtests + audit logging
- Compliance reports and exports
- Real-time evaluation via SDK
- Tool call validation
- Session chain tracking
- Drift monitoring and alerts
- Cost alerting
- DLP scanning
- Tamper-evident audit integrity
- Compliance mapping — rules linked to regulations
- Compliance reports and exports
- Local evaluation mode — zero data egress
- Everything in Compliance
- Human review (HITL) workflows
- Synthetic testing and scheduling
- A/B experiments across models
- Benchmark suites
- Industry control pack templates
- Private and sovereign deployment options
- Dedicated support
- White-label & MSSP options available
Typical customers recover the cost from a single prevented incident. One blocked unauthorised transfer, one avoided compliance fine, one stopped agent loop — and DriftGard has paid for itself.
Designed for production: sub-10ms latency · fail-safe fallback handling · scales to high-volume AI workloads
Frequently asked questions
Is DriftGard a monitoring tool?
No. DriftGard is a runtime enforcement layer. It decides what AI is allowed to do, blocks violations before they reach users, validates tool calls before they execute, and creates tamper-evident proof that your AI followed the rules.
How does it handle AI agent tool calls?
Every tool call is validated against a zero-trust allowlist. Parameter-level rules enforce type, range, regex, and custom expressions. Cross-parameter checks catch things like self-transfers. DLP scans tool arguments for PII and secrets before execution.
What is session chain tracking?
When an agent makes multiple decisions in a conversation, DriftGard links them together with session IDs and parent links. You see the full chain — which decision led to which action, in what order. Sequence numbers detect out-of-order arrivals. Chain depth limits stop infinite loops.
What happens if DriftGard goes down?
Your app stays up. The SDK includes a circuit breaker that skips API calls after consecutive failures. You configure fail-open (allow everything) or fail-closed (block everything). DriftGard is never a single point of failure.
How do you prove records haven't been tampered with?
Every decision is hashed at write time. Hourly Merkle roots provide a second verification layer. On-demand verification recomputes hashes and compares against stored values — a mismatch means the record was changed.
What compliance frameworks do you support?
EU AI Act, ISO 42001, NIST AI RMF, and Australian Privacy Act including APP 1.7 transparency statements. Reports are generated as signed PDFs with tamper-evident verification.
How quickly can we start?
A pilot audit takes days. SDK integration is a single npm install or pip install. Industry templates activate in minutes. Start with post-response monitoring and add real-time enforcement when ready.
Can we run DriftGard without sending patient data to your servers?
Yes. Local evaluation mode runs the entire engine inside your environment via compiled WebAssembly. No prompt, response, or conversation content leaves your trust boundary. You can optionally report verdict metadata (allowed/blocked, risk score, violation IDs) for compliance dashboards — without any patient content. Built for mental health, clinical, and sovereign deployments.
Can we enforce different rules per state or country?
Yes. Jurisdiction-scoped rules let you tag each rule with the jurisdictions it applies to — AU-VIC, US-CA, EU, or any custom code. Pass the user's jurisdiction in the evaluate request and only matching rules fire. Global rules (no jurisdiction tag) fire for everyone. One control pack handles all jurisdictions.
Resell AI governance under your brand
MSSPs, system integrators, and consultancies use DriftGard as their white-label AI compliance platform. Your brand, your clients, our engine.
Ideal for MSSPs, consultancies, system integrators, and compliance firms.
Request a demo
or pilot audit
What you'll see in the demo
Common starting point
Start in observe mode — profile real AI behaviour from historical logs, generate control policies, then enable real-time enforcement via SDK when ready.
"We fixed AI risk after the first incident."
DriftGard prevents the incident.