Pillar 1
Safety
- PII redaction across inputs, payloads, and results
- Reduce data leakage and audit failures
- Defensible AI decision records
Why Companies Can't Deploy AI Agents Without Governance
AI agents act like digital workers — but they don't naturally follow rules.
Left ungoverned, AI agents will:
Access data they shouldn't
Take unauthorized actions
Hallucinate when blocked
Leave no audit trail
Create regulatory exposure
Companies need to:
- Control what agents do
- Govern which tools they use
- Restrict the data they see
- Audit every action
- Prove compliance
ContextGate makes AI agents behave like safe, governed, compliant employees.
or
Triggers
Chat
Webhook
Schedule
Context Gate
PII Protection
Redact:EMAIL, PHONE, SSN
Model
Google Geminigemini-2.5-pro
Instructions
You are a finance ops agent. Always redact PII before…
Creativity1.0
Toolbox
Salesforce Behaviorpolicy
CONNECTIONS
Salesforce42 tools
HubSpot18 tools
SAP S/4HANA36 tools
Why This Is Different
Vendors Govern Models.
ContextGate Governs Agents.
Most AI governance tools focus on the LLM, the data store, or the retrieval index. None of them control what an agent actually does. ContextGate owns the missing layer.
Layer 1
Model governance
Controls the LLM — choice of provider, prompt filters, model-level safety.
Layer 2
Data governance
Controls databases and warehouses — what data exists, who can query it.
Layer 3
Retrieval governance
Controls what content is retrieved and surfaced to a model at inference time.
The missing layer
Agent governance
Controls what agents can do — tools, data access, actions, and a full audit trail.
Capability
Model / Data / Retrieval Governance
ContextGate (Agent Governance)
Primary scope
The model, dataset, or retrieval index
The agent — its tools, data, and actions
Tool / MCP control
Out of scope (lives in app code)
Per-agent tool permissions via MCP
Action authorization
Not enforced
Policy-based controls on every agent action
PII redaction
Prompt-level only
Inputs, payloads, tool calls, and results
Audit trail
Model usage logs
Every agent decision, tool call, and outcome
Identity & access
User-level (the human caller)
Agent-level — like an access badge for digital workers
Model independence
Tied to one provider
Same governance across any LLM
The Solution
Turn Agents Into Governed Digital Employees
ContextGate gives AI agents the same structure, rules, and oversight that real employees have — so the business can deploy them safely.
Pillar 2
Governance
- Tool, data, and action permissions per agent
- Workflow approvals for high-risk steps
- Like an access badge — agents only open allowed doors
Pillar 3
Performance
- Zero-copy SQL access to company data
- Reduce hallucinations with grounded retrieval
- Improve answer accuracy under governance controls
Live preview
A governed agent in action.
When the Finance Ops agent tries to push a bank account into Salesforce, ContextGate redacts the PII before the prompt leaves your perimeter and blocks the cross-system write that wasn't on its allowlist — while still letting the legitimate HubSpot call through. Every step is logged.
- ✓PII redacted before it reaches the model
- ✓Off-policy tool call blocked at the proxy
- ✓Every decision recorded for audit
Finance Ops Agent
Governed Trigger byChatPublish a chat interface for your users, WebhookTriggered by external HTTP calls, ScheduleRuns automatically on a cron schedule, EventsReacts to new emails, file uploads, alerts
Comply
Guarantee Compliance Without Breaking Functionality
Upload your policy documents and specifications — ContextGate's AI assistant builds production-ready, governed agents for you. No technical knowledge required.
PII Redaction
Automatically detect and redact emails, phone numbers, SSNs, credit cards, and custom patterns.
Policy from Docs
Upload your privacy policy or compliance document to auto-generate governance rules.
LLM Governance
Use AI-powered checks to verify intent, consent, and data minimization compliance.
PII Redaction Rules
Select which PII types to detect and redact
Governance Checks (LLM-based)
LLM-powered content validation rules
GDPR Data Purposellm
Validation prompt
Verify any access to personal data aligns with the stated processing purpose declared in the request context.
LLM Model
gpt-4o-mini
Action on Failure🛑 block
Enforce OnInput
Consent Verificationllm
Validation prompt
Reject requests when the upstream consent flag is missing or expired for the data subject in question.
LLM Model
gemini-2.5-flash
Action on Failure⚠️ warn
Enforce OnInput
Data Minimisationllm
Validation prompt
Block tool calls that request fields beyond the minimum needed for the agent’s stated task.
LLM Model
claude-haiku-4.5
Action on Failure🛑 block
Enforce OnOutput
Agent-to-Agent Governance
The Workspace Assistant Governs Your Agents
Once you have ten, fifty, a hundred governed agents in production, you need an agent that supervises the agents. ContextGate's workspace assistant runs continuous audits and remediates policy violations — across every agent, on a schedule, autonomously.
Workspace Assistant
Compliance audit · 18 agents
Triggered by audit_agents · Finished 12s ago
14Pass
4Fail
Missing: IBANMissing: Sort code
Missing: Person names
Violation: Model
Violation: Tools
GDPRHIPAAISO 42001
Continuous audits
Run policy checks across every agent on a schedule, on every config change, or on demand — without writing one-off scripts.
Catch violations early
Flag agents that fail any rule — new tools added, redactions disabled, non-allowlisted models — before an auditor or regulator does.
One-click remediation
The assistant proposes the fix, links the policy gap to a remediation, and applies it once you approve — keeping a full audit trail.
MCP Connectors
Connect to 0+ Apps
Give your AI agents secure access to real data. Use our pre-built connectors, or connect to any MCP server URL—all governed by your policies.
0 apps
OAuth & API Keys
Secure authentication flows with credentials stored encrypted.
Real-time Audit
Every data access logged and visible in your dashboard.
Policy Enforcement
PII redaction and access rules applied to all connector data.
Control
Full Visibility on Every Agent Decision
Monitor, filter, and audit every request in real-time. Get dashboards with key metrics and drill down into individual tool calls with full request/response details.
Total Requests
12,847
+12%
Blocked
234
1.8%
PII Redactions
1,203
-5%
Avg Latency
120ms
-8ms
Activity Over TimeLast 7 days
Passed Warned Blocked
Policy ActionsLast 24h
Allowed85%
Redacted10%
Blocked5%
Top Tools by UsageLast 24h
Recent Policy Actions3 new
Blocked bulk delete attempt
PII redacted in Slack tool payload
New toolbox "Analytics" created
Real-Time Metrics
Track request volume, policy actions, and response times across all your agents in one dashboard.
Audit Logs
Every request is logged with full context. Filter by user, tool, policy, status, and date range.
Instant Alerts
Get notified when policies block requests, rate limits approach, or anomalies are detected.
Vendor Agnostic
Works With Any Model Vendor
Stay independent from model vendors. ContextGate sits between your application and any LLM provider, so you can switch models without changing your governance rules.
OpenAI
Anthropic
Google Gemini
Groq
OpenRouter
GitHub Models
Azure OpenAI
Bring Your Own
Switch Freely
Change models without touching your governance configuration.
Same Governance
One set of policies applied consistently across all providers.
No Lock-in
Negotiate better rates and avoid vendor dependency.
FAQ
AI Agent Governance, Answered
The questions enterprise buyers, risk teams, and AI platform leads ask before deploying agents.
What is AI agent governance?
AI agent governance is the layer of controls, permissions, and audit logging that determines what an AI agent is allowed to see, which tools it can use, what actions it can take, and how every decision is recorded. It is distinct from model governance (which controls the LLM) and data governance (which controls the underlying data stores).
Why do companies need AI agent governance?
Agents are not chatbots — they take actions, use tools, and access systems. Without governance, they can expose regulated data, execute unauthorized actions, hallucinate when they lack grounded data, and leave no defensible audit trail. No regulated company can deploy agents at scale without it.
How is agent governance different from model governance?
Model governance controls the LLM — choice of provider, prompt filters, model-level safety. Agent governance controls what an agent built on top of that model is allowed to do — its tools, its data access, its actions, and its audit trail. ContextGate owns this missing layer.
What are rogue AI agents?
Rogue agents are AI agents that act without supervision — they access data they should not see, take actions they are not authorized to take, leave no records, and hallucinate when they lack the right data. Governance turns rogue agents into governed digital employees. See example governed agents for what this looks like in practice.
How does ContextGate control what agents can do?
ContextGate enforces policy-based controls on every agent action: which MCP tools an agent can call, which data sources it can read, which workflows require approval, and which outputs are blocked or redacted. Policies are versioned and applied consistently across every model and connector.
How does ContextGate protect sensitive data?
ContextGate detects and redacts PII (emails, phone numbers, account numbers, SSNs, custom patterns) across inputs, tool payloads, model calls, and results — before sensitive data is exposed to a vendor model or stored in logs. See the privacy policy for how we handle data.
Does ContextGate support MCP and tool access?
Yes. ContextGate is an MCP-native governance layer. Agents discover tools via MCP, and ContextGate brokers every tool call with policy checks, redaction, and audit logging — across 2,000+ pre-built connectors or any MCP server URL.
How does ContextGate reduce hallucinations?
Hallucinations spike when agents cannot reach the right grounded information. ContextGate gives agents safe, governed access to company data via a zero-copy SQL engine — so they answer with real data instead of guessing — while keeping every retrieval under policy controls.
How does ContextGate help with compliance and audits?
Every agent decision, tool call, redaction event, and policy outcome is logged with full context. Compliance teams get an evidence trail that maps to GDPR, HIPAA, SOX, and ISO 42001 controls — without the engineering team having to build custom logging.
Is ContextGate model-agnostic?
Yes. ContextGate sits between your application and any LLM provider — OpenAI, Anthropic, Google, Azure OpenAI, open-source via Ollama, or your own. Switch models without rewriting your governance rules.
Our Team
Adam Cooke
Founder & CEO
Adam is a second-time founder who previously co-founded an enterprise data visualization platform. He brings deep expertise in R&D, presales and positioning data integration tools specifically for enterprise clients.
John Dreic
Chief Marketing Officer
10+ years driving large-scale change, leading content strategy, AI adoption, and digital transformation across global financial institutions. Built in-house creative and automation teams, implemented AI workflows, and delivered multimillion-dollar efficiency gains.
Sandor Szabo
MBA, CIPP US - Compliance Expert
Compliance and privacy expert ensuring ContextGate meets the highest standards of data protection and regulatory requirements.
Brian Munz
Dev Relations Expert
Developer advocate and community builder, bridging the gap between ContextGate's technology and the developer ecosystem.
Sean Farrington
Board Advisor
Strategic advisor providing guidance on enterprise growth and market expansion.
Gary Hobbs
Board Advisor
Board advisor with extensive experience in enterprise software and go-to-market strategy.
Get in Touch
Ready to govern your AI agents? Let us know about your use case and we'll help you get started.