AI agents
Build AI agents that execute real work with responsible guardrails.
Create task-specific agents that use tools, retrieve context, follow permissions, measure quality, and escalate when human judgment is required.
Business problems
- Teams want AI assistance but need control
- Prompts fail in real workflows
- Agents need system access
- Quality must be measurable
Measurable outcomes
- Less repetitive decision work
- Higher response consistency
- Clear escalation paths
- Reusable agent patterns
Capabilities
- Agent architecture
- Tool calling
- Evaluation harnesses
- Memory design
- Fallback routing
- Supervisor controls
Example use cases
- Sales research agents
- Knowledge support agents
- Operations coordinators
- Data analyst copilots
- Internal service desk agents
Delivery approach
- Define task boundary
- Design tools and permissions
- Build evals
- Pilot with real users
- Monitor and improve
Integrations and technology
- OpenAI-compatible models
- Vector databases
- Slack/Teams
- CRM
- Internal APIs
Security and governance
- Permission scoping
- Prompt/version control
- Quality thresholds
- Human approval gates
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