Production AI Workflows
Turn a manual process into a controlled AI operating system.
We design and implement workflows that gather context, apply AI, follow business rules, call approved tools, involve people at the right points, and leave a complete operational record.
Best-fit workflows
- · Repetitive but not fully deterministic
- · High volume or high coordination cost
- · Multiple systems or data sources
- · Clear business rules and exception paths
- · Measurable cycle time or quality baseline
- · Human review is possible for uncertain or high-impact cases
What we build
- · Intake and classification
- · Context assembly
- · Retrieval and source grounding
- · Decision support
- · Draft generation
- · Tool calls and system updates
- · Review queues
- · Escalation and exception handling
- · Audit history
- · Monitoring and evaluation
What is included
- 1. Workflow mapping
- 2. Data and integration design
- 3. Model and orchestration strategy
- 4. Security and permission boundaries
- 5. Human approval design
- 6. Evaluation suite
- 7. Production deployment
- 8. Monitoring and runbooks
- 9. Documentation and handoff
What we do not recommend
- · Fully autonomous action where consequences are high and review is practical
- · Replacing clear deterministic rules with an LLM
- · Launching without representative test cases
- · Giving a workflow broad tool or data access by default
- · Binding the architecture unnecessarily to one model vendor
Start with one bounded workflow.
We will identify the inputs, decisions, actions, controls, and evidence required for a production pilot.