Workflow and decision map
Inputs, sources of truth, rules, model decisions, human gates, side effects, and exception paths shown in one operating view.
AI automation / Controlled operations
Automate the repeatable work. Keep judgment visible.
Opportunity Relay designs narrow AI and workflow pilots around a real operating decision. Sources, rules, review points, side effects, and failure behavior are made explicit before the system is trusted with more work.
When this service fits
Start with the delivery condition, not the technology.
A testable pilot that shows what the system can do, where a person remains responsible, and what evidence would justify expanding it.
- Teams repeatedly classify, extract, route, summarize, or draft from known business inputs.
- An agency needs a controlled AI layer inside a client workflow rather than a standalone chatbot.
- A product has an AI concept but no evaluation, privacy, or failure-handling plan.
Delivery scope
The release is made of reviewable outputs.
Exact scope depends on the repository, product, integrations, and acceptance criteria. These are the working categories—not a promise that every project needs every item.
Pilot implementation
A narrow working flow with structured outputs, deterministic checks, approval boundaries, and test fixtures.
Evaluation set
Representative examples, expected behavior, abstention rules, and failure cases used to evaluate changes before release.
Operational controls
Logging, retry and idempotency choices, cost visibility, privacy notes, and a documented human fallback.
Questions resolved before the schedule is trusted.
Unanswered operating questions become implementation rework. They belong in the scope conversation, not at the end of QA.
- 01
What exact decision or repeated action should the pilot improve?
Clarify the intended result and who can approve it.
- 02
Which information may the system use, retain, or send to a provider?
Make system, data, and responsibility boundaries explicit.
- 03
What evidence makes an output acceptable, uncertain, or unsafe to use?
Agree on evidence before calling a behavior complete.
- 04
Which external side effects require approval, idempotency, or rollback?
Assign ownership for release and operation.
Working sequence
A visible path from uncertainty to handoff.
Each phase creates an artifact the buyer can inspect. The work does not depend on a final reveal.
- 01
Define the decision
Choose one repeated workflow, baseline it, and define what a useful outcome means without assuming automation is the answer.
Output: Pilot charter and baseline - 02
Design the controls
Map approved sources, model boundaries, deterministic rules, human review, privacy, and failure behavior.
Output: Control and data-flow map - 03
Build and evaluate
Implement the narrow flow and test representative, adversarial, incomplete, and duplicate inputs.
Output: Working pilot and evaluation record - 04
Decide whether to expand
Compare the pilot with the baseline and document the operating cost, error profile, and next decision.
Output: Go, revise, or stop recommendation
RelayOps makes approval boundaries inspectable
RelayOps demonstrates deterministic routing, explicit states, idempotent retries, a human approval gate, and a local audit trail. It is not presented as a deployed client integration.
Scope boundaries
A clear no is part of reliable delivery.
These boundaries prevent the service from implying proof, access, or outcomes the current public evidence does not support.
- Autonomous high-impact decisions without accountable human review
- Unapproved production data in a public or reference environment
- ROI promises before a real baseline and operating cost are known
Questions to settle before kickoff.
Commercial terms, account access, confidentiality, ownership, communication cadence, and support are confirmed for the actual engagement rather than implied on a marketing page.
01Does every automation need AI?
No. Deterministic rules are easier to test and operate when they can solve the problem. AI belongs only where the input genuinely requires interpretation and the error boundary can be controlled.
02Can a pilot connect to our CRM?
Potentially, but the data, credentials, sandbox availability, rate limits, ownership, and rollback path must be scoped first. A reference build is not proof of a production CRM integration.
03How is success measured?
The pilot should compare a small number of operating signals, such as handling time, correction rate, completion rate, or review effort. The appropriate measures depend on the actual workflow and baseline.
AI automation / Fit conversation
Define the release before committing to the build.
A useful first conversation covers the current state, intended release, open decisions, evidence available, and the constraints that cannot move.