AI AGENTS / BUSINESS AUTOMATION
AI agents connected to your business systems.
For teams integrating language models, tool-calling workflows and conversational agents with real APIs and accountable operations.
SYSTEM RISK / REAL FAILURE CONDITIONS
The boundary is the problem.
A model response cannot authorize a payment, customer-record change or privileged action. Tool access belongs to an authenticated identity and a server-enforced permission decision.
TRUST FLOW / ILLUSTRATIVE ARCHITECTURE
- 01Customer request and authenticated session
- 02Agent planning and constrained tool selection
- 03Backend permission and approval checks
- 04Audited execution, retries and failure recovery
Reference architecture / representative request flow.
NEGATIVE-PATH VERIFICATION
What we'd test
- Untrusted prompt attempts to elevate tool permissions
- Cross-account tool request with a legitimate session
- High-impact action without human approval
- Timeout and retry without duplicate side effects
EXPECTED PROJECT OUTPUTS
What the team receives
- Tool and permission contracts
- Agent integration and evaluation fixtures
- Negative-path tests and human-review controls
- Deployment monitoring and handoff
Scope, access, deliverables and acceptance conditions are agreed before work begins.
RELATED PROJECT / RESEARCH
Interactive AI agent authorization demo
Browser-based tool policy demonstration
Relevant stack: Python · TypeScript · LLM APIs · MCP · OAuth / OIDC
Discuss a specific boundary in your system.
Tell us the platform, the failing workflow, any compliance or safety constraints, and what success would look like. No confidential production data is needed in the first message.
Request a scoped review