ONE CONNECTED
PERSPECTIVE
Strategy, creative direction, user experience, technology, production, and quality work as one connected service perspective. The exact scope is confirmed after discovery.
POSSIBLE CAPABILITIES
Build around the task, not a technology list
Each area begins with a problem to investigate. A first engagement may clarify feasibility and direction before implementation is agreed.
01
Knowledge search and retrieval
Explore trusted sources, retrieval quality, permissions, citations, and update requirements.
02
Workflow automation and routing
Reduce repetitive work through appropriate triggers, routing, approvals, and human review.
03
Content and customer-support copilots
Support drafting or lookup tasks without implying unsupervised customer communication.
01
Model and API integration
Consider approved services, data boundaries, permissions, operational cost, and platform constraints.
02
Evaluation, guardrails, and human review
Define quality checks, edge cases, escalation, and monitoring.
03
Information and experience design
Shape how people understand inputs, outputs, uncertainty, and the next action.
START WITH YOUR CONTEXT
Who this is for
These are signals that a focused discovery conversation may be useful, not promises that AI is the right solution.
01
Find information
Teams need to locate trusted internal information across existing sources.
02
Route repetitive work
Repeated requests or handoffs could benefit from a clearer workflow.
03
Support teams
Content or customer-service teams want to explore assistance while retaining review.
04
Extend an experience
An existing product or website may have a defined place for helpful assistance.
05
Test the premise
The organization needs evidence that automation will be useful before investing.
A PROPOSED ENGAGEMENT PATH
From a real task to a reasoned decision
A responsible approach reduces uncertainty before a production system is promised.
01
Understand
Define the task, workflow, information sources, and the point where automation would be useful.
02
Prototype
Test representative examples, edge cases, and likely failure modes.
03
Evaluate
Compare output quality, risks, human-review needs, and operating cost.
04
Connect controls
If appropriate, integrate permissions, data boundaries, documentation, monitoring, and ownership.
DECISION GUIDANCE
AI or simpler automation?
A useful recommendation starts with the shape of the work. The answer may be a model, deterministic automation, improved search, or a combination.
- Use AI when information is unstructured or the work requires interpretation with controls.
- Consider simpler automation when rules are deterministic and inputs can be validated.
- Prototype against representative examples before making a production claim.
- Define human review, escalation, and logging before launch.
- Identify approved data sources and permissions.
- Confirm where outputs may be wrong, incomplete, or inappropriate.
EVIDENCE / APPROVAL REQUIRED
Show the work when it is approved
Approved AI examples will describe the task, controls, evaluation approach, and verified result without unsupported performance claims.
01
Approved evidence placeholder 01
Verified project context, approved contribution, relevant deliverables, and an attributable result will appear here.
02
Approved evidence placeholder 02
Verified project context, approved contribution, relevant deliverables, and an attributable result will appear here.
03
Approved evidence placeholder 03
Verified project context, approved contribution, relevant deliverables, and an attributable result will appear here.
Only verified, approved client names, claims, metrics, quotations, and outcomes should replace these placeholders.
GOOD QUESTIONS
AI development FAQs
START WITH THE RIGHT QUESTIONS
Discuss your AI project
Tell us where work gets stuck, what affects quality, and where a clearer decision or response would create value.
Submitting this form starts a project conversation. Scope, timing, responsibilities, and outcomes are confirmed before work begins.