AI agents are powerful.
Ungoverned agents are dangerous.

AI governance platform + expert integration services. We don't just give you tools — we help you deploy them. Security, access control, and full audit trails for every agent decision.

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The Problem

AI agents without guardrails are a liability

AI agents can read your databases, call your APIs, send emails on your behalf, and make decisions that affect real customers. Without governance, every agent is an insider threat.

!

Credential Sprawl

Every agent-to-tool connection requires its own API keys, OAuth tokens, and service accounts. Credentials scatter across environments with no central control.

!

Invisible Actions

An agent deletes a production record, sends a customer email, or leaks PII in a response. Without audit trails, nobody knows until the damage is done.

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Unbounded Access

Most agent frameworks give every agent access to every tool. There's no concept of least privilege. A sales assistant can reach engineering databases.

The Solution

Three gateways. Complete control.

WorkingAgents puts a governance layer between your agents and everything they touch.

AI Gateway

Unified proxy to 250+ LLMs. One API, automatic failover, smart routing by cost or latency, minimal overhead. Your agents never talk to model providers directly.

AI Agent Gateway

Control plane for agentic workflows. Multi-step execution with retries, timeouts, and fallbacks. Works with any agent framework via HTTPS and Secure WebSocket (WSS) APIs.

🔗

MCP Gateway

Enterprise hub for Model Context Protocol. Centralized tool registry, per-user token management, permission boundaries, and guardrails on every tool call.

Why Now

The agentic era demands a new security model

Security

Your data never leaves your environment

WorkingAgents deploys inside your VPC, your data center, or your air-gapped network. The platform orchestrates workloads without extracting data. No third-party ever touches your information.

  • Designed for SOC 2 Type 2 compliance
  • HIPAA-ready architecture for healthcare workloads
  • GDPR-ready with data residency controls
  • Self-hosted or cloud — your choice
// Data flow
Agent Request
  → WorkingAgents Gateway (your VPC)
    → Auth check
    → Guardrail scan
    → PII redaction
  → Tool execution (your infra)
  → Audit log (your storage)

Zero data egress. Full audit trail.
Access Control

Every agent gets exactly the access it needs

Virtual MCP Servers let you define permission boundaries per team, per role, per use case. A sales agent sees CRM tools. An engineering agent sees deployment tools. Neither sees the other's data.

  • Four-layer authentication (gateway, team, service, custom)
  • Capability-based access control
  • Per-user, per-service, per-endpoint rate limits
  • Single token replaces scattered credentials
// Virtual MCP Servers

Sales Team Server
   CRM read/write
   Document generation
   Knowledge search
  × Database admin
  × Deployments

Engineering Server
   GitHub / CI-CD
   Issue tracker
   Deployments
  × CRM data
  × Financial records
Observability

See everything. Miss nothing.

Every agent action, tool call, model request, and guardrail evaluation is logged. When something goes wrong — and it will — you know exactly what happened, who triggered it, and why.

  • Token-level cost attribution by user, team, and model
  • Request-level inspection with full prompt and response
  • P99/P90/P50 latency tracking per endpoint
  • Structured logging and request tracing for distributed debugging
// Audit log entry
{
  "agent": "sales-assistant",
  "user": "[email protected]",
  "tool": "crm.search_contacts",
  "args": { "query": "Acme Corp" },
  "guardrails": {
    "pii_check": "passed",
    "injection_check": "passed"
  },
  "latency_ms": 42,
  "cost_usd": 0.0018
}
250+
LLMs supported
3x
Gateway layers
4-layer
Authentication
100%
Audit coverage
Guardrails

Protect every interaction at three checkpoints

Automated safety checks before, during, and after every tool call your agents make.

Pre-Execution

Validate inputs before any tool runs. Block SQL injection, path traversal, prompt injection, and malformed requests before they reach your systems.

Real-Time

Monitor execution and require human approval for high-risk operations. "The agent wants to delete a production table — approve or deny?"

Post-Execution

Inspect outputs before they reach the agent. Redact PII, mask credentials, filter confidential data. Sensitive information never leaves your perimeter.

GuardrailWhat It Catches
Prompt injection preventionBlocks "ignore all previous instructions" and similar attacks
PII detection & redaction20+ categories: SSNs, credit cards, emails, phones, addresses
Content safetyHate speech, self-harm, violence with configurable thresholds
Topic filteringBlock specific domains: medical advice, legal counsel, financial tips
Custom rulesYour own policies, your own logic, enforced at the gateway
The Case for Governance

Why this isn't optional anymore

Every previous wave of technology created a new category of risk. Cloud computing created cloud security. Mobile apps created app security. APIs created API security. Each time, organizations learned the hard way that the same capabilities that make technology powerful also make it dangerous when ungoverned.

AI agents are the next wave, and the risks are fundamentally different. A misconfigured API endpoint leaks data when someone finds it. An ungoverned AI agent actively seeks out data, makes decisions about it, and takes actions based on those decisions — continuously, at scale, without human review.

The difference between a tool and an agent

A tool waits for instructions. An agent makes decisions. When your AI can decide to query a database, draft an email, and send it — all in a single chain of reasoning — the governance model that worked for tools doesn't work for agents. You need controls at every step of the chain, not just at the entry point.

What ungoverned AI agents look like in practice

Credential sprawl. Five agents connecting to ten tools means fifty sets of credentials scattered across config files, environment variables, and secret managers. No central inventory. No rotation policy. One leaked key exposes everything that agent could access.

Shadow actions. An agent deletes a record it shouldn't have. An agent sends an email with confidential pricing. An agent surfaces PII in a chat response. Without audit trails, these events are invisible until a customer complains or a regulator asks questions.

Privilege escalation. An agent designed for customer support discovers it can also access the billing database, the HR system, and the deployment pipeline — because nobody scoped its permissions. It's not malicious. It's just using every tool available to answer the question it was asked.

Cost explosions. An agent stuck in a retry loop burns through thousands of dollars in API calls overnight. Without token-level monitoring and budget enforcement, you find out when the invoice arrives.

What governed AI agents look like

Least privilege. Every agent gets exactly the tools it needs and nothing more. Virtual MCP Servers define permission boundaries per team and use case. The sales agent can't reach engineering tools. The support agent can't modify billing records.

Complete visibility. Every tool call, every model request, every guardrail evaluation is logged with the user, the agent, the inputs, the outputs, and the cost. When the CEO asks "what is our AI doing?" — you have the answer.

Automated safety. PII is redacted before it enters agent context. Prompt injection is blocked before it reaches the model. High-risk actions require human approval. The guardrails run at the gateway level — they work regardless of which framework or model the agent uses.

Cost control. Token-level attribution shows exactly which team, user, and use case is consuming what. Budget caps prevent runaway spending. Smart routing sends simple queries to cheaper models and complex queries to capable ones.

Today
With WorkingAgents
🔑
Credentials managed per integration
Each agent-tool connection maintains its own API keys, tokens, and service accounts across environments.
Single token per user, centrally managed
One Personal Access Token replaces scattered credentials. The gateway handles rotation and refresh.
👁
Audit trails built per application
Each team builds its own logging. Coverage is inconsistent and forensic investigation requires stitching logs together.
Every action logged automatically
Tool calls, model requests, guardrail evaluations, and permission checks — all captured at the gateway with full context.
🔓
Broad access, manually scoped
Agents get access to all available tools. Restricting permissions requires custom code per framework and per deployment.
Least-privilege, enforced by policy
Virtual MCP Servers define exactly which tools each team can use. No custom code — just configuration.
💰
Usage reviewed at invoice time
API costs are discovered monthly. No real-time visibility into which teams, agents, or use cases are driving spend.
Real-time cost attribution by team and model
Token-level tracking with budget caps and alerts. Smart routing sends simple queries to cheaper models automatically.
👥
Safety checks built into each agent
PII handling, injection prevention, and content filtering are implemented per agent. Coverage depends on each developer.
Automated guardrails at every checkpoint
Pre-execution, real-time, and post-execution guardrails at the gateway — applied uniformly regardless of framework or model.
🚀
Each team deploys agents independently
Teams adopt AI at their own pace with their own tooling. No unified view of what agents exist or what they can do.
Structured scaling with full visibility
Progressive adoption from a single gateway to full platform governance. Central registry of all agents, tools, and permissions.
Built By Engineers

Built by engineers, for engineers

WorkingAgents is built by James Aspinwall — a software engineer who got tired of watching AI agents run unsupervised. Every feature exists because a real production system needed it.

We work directly with your team: integration, customization, training, and ongoing support. No ticket queues. No layers of account managers. You talk to the people who build it.

Build AI agents that your security team will approve

Platform + hands-on expertise. We help you deploy AI agents with the governance your organization demands.

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