AI agent and workflow automation development
Give the agent one accountable job before giving it autonomy.
For teams with a repeatable information or routing task that can be connected to trusted sources, tested against representative cases, and handed back to a person when needed.
- Typical first release
- A bounded pilot commonly takes 4–8 weeks; production expansion follows evaluation evidence and integration access.
- Engagement
- Paid workflow discovery and pilot, followed by evidence-gated production expansion.
The operating problem
Start with the constraint, not the deliverable.
Generic assistants sound capable in a demonstration but fail when sources conflict, permissions matter, an action has consequences, or the request should be refused. The workflow needs boundaries before it needs a personality.
Good fit for
- Customer enquiry qualification and approved knowledge retrieval
- Internal document search, summaries, classification, and routing
- Structured extraction from recurring documents or conversations
- Controlled actions into CRM, ticketing, calendar, or reporting systems
What is delivered
A production scope with named boundaries.
Workflow, source, action, confidence, and human-handoff boundaries
Retrieval and orchestration layer with selected models and provider abstraction
Structured outputs, validation, permissions, and downstream integrations
Representative evaluation set including refusal and exception cases
Logs, cost and latency visibility, feedback capture, and failure handling
Deployment runbook and owner responsibilities for source freshness and review
Delivery path
Four stages, each with a usable output.
- 01
Bound the job
Define trigger, trusted inputs, expected output, actions, exceptions, and accountable human owner.
- 02
Build the evaluation
Create ordinary, missing-data, conflicting, adversarial, multilingual, refusal, and escalation cases.
- 03
Connect the loop
Implement retrieval, reasoning, validation, permissions, integrations, and visible handoff.
- 04
Observe
Launch beside the current process and measure corrections, routing, cost, latency, and completed workflow outcomes.
Related implementation
CIOS conversation orchestration
A productized deployment pattern for approved knowledge, structured lead fields, routing rules, and human escalation.
Open the case or product explanation →Questions before scoping
Useful answers before a sales call.
Which model or provider do you use?
The choice depends on the task, language, privacy, latency, tool use, and cost. We keep business rules and evaluation separate from a single model where practical.
Can the agent write into our CRM or book meetings?
Yes where the platform API and permissions allow it. Write actions are scoped separately from read actions and may require validation, confirmation, idempotency, and audit logs.
How do you reduce hallucinations?
We constrain sources and actions, validate structured output, evaluate representative cases, expose uncertainty, and design refusal and human handoff. No implementation makes a language model infallible.
Start with context
Bring the workflow, constraint, and desired decision.
We will respond with focused questions and the smallest credible first release.