AI AGENTS / AUTOMATION & SECURITY
AI Agent Development & Security
Put AI to work. Keep your systems in control.
Integrate tool-using AI agents with real APIs and business workflows, without letting model output bypass identity, authorization, approval or operational safeguards.
AI TOOL EXECUTION / ENFORCEMENT
01 / FLOW
User + agent
Proposed action
02 / CHECK
Policy gateway
Permission + approval
03 / FLOW
Business API
Logged execution
Engineering boundaries · design → test → delivery
CAPABILITIES / TECHNICAL COVERAGE
The expertise your team needs, focused on the work that matters.
Teams introducing agent-assisted support, automation or AI-enabled product features.
LLM API integration
Agent permissions & isolation
Human approvals
Prompt-injection and abuse testing
Evaluation & observability
OUR APPROACH
From first conversation to delivered results.
Define a bounded task
Choose the user goal, data sources, allowed operations and measurable success conditions.
Integrate the right tools
Use authenticated API gateways and server-enforced action policies.
Test the agent under pressure
Evaluate prompt injection, identity changes, partial failures and unsafe tool requests.
Ship with control
Add audit logs, human review, retries, rollback and operational ownership.
TECHNICAL EXAMPLE / SYSTEM BOUNDARIES
Agent tool calls behind an authorization boundary
Model output proposes an action. The server independently checks identity, resource ownership and approval before executing a tool. This distinction matters more than prompt wording.
Try the tool authorization demoREFERENCE WORKFLOW
- 01
Agent
Proposes a tool invocation
- 02
Policy
Checks user, resource and approval
- 03
Execution
Allow or deny; audit the outcome
An engineering reference flow, not a customer engagement.
DELIVERABLES
What your team receives.
- Implemented agent workflows and API adapters
- Tool permission and approval matrix
- Evaluation scenarios and negative-path tests
- Runtime telemetry, handoff and deployment plan
BUSINESS BENEFITS
Clarity for the people responsible.
Automate useful work safely
Keep high-impact actions accountable
Measure reliability beyond prompt quality
TECHNICAL WALKTHROUGH
AI agent tools: permissions before execution
An original visual walkthrough of tool allowlists, user permissions and human approval checks.
Read the walkthrough transcript
- The agent receives a user request and selects a tool that could change a business record.
- Model output is treated as untrusted input; the backend authorizes identity, resource and action separately.
- Privileged or irreversible actions require an explicit approval step before execution.
- Replays, prompt injection and failed retries must be tested and logged without exposing secrets.
SPECIALIZED SERVICES / RESOURCES
Explore the work in more detail.
AI agent integrations
Tool orchestration and application integration
Learn MoreAgent security
Runtime and tool boundary controls
Learn MoreAgent authorization demo
Interactive browser model
Learn MoreFrequently asked questions
Can an agent act on behalf of a user?
Yes, for operations the authenticated user is authorized to perform and that the backend has explicitly permitted. High-impact actions can require human approval.
Does prompt engineering replace security testing?
No. Tool permissions, data isolation, prompt-injection testing, auditability and failure recovery must also be designed and tested.
Let's work through your next challenge.
Tell us what you're building, securing or trying to improve.