Services

Assess the value.
Design the work.
Deploy the improvement.

A practical path from a recurring problem to a workflow your team can use and own.

Start with an AI Opportunity & Value Assessment. Design and deployment are separate paid decisions, supported by evidence and readiness.

Tell us about your workflow

Stage 1 / Decide whether to invest

AI Opportunity & Value Assessment

A useful decision even when AI is not the answer.

We examine ownership, frequency and volume, labor and delay, rework and failure points, inputs, outputs, decisions, and handoffs. We review available data and its sensitivity, current tools and constraints, implementation burden, and adoption, governance, and operational risks.

Compare five alternatives

Leave the workflow unchanged.
Simplify or clarify the process.
Use conventional deterministic automation.
Use an AI-assisted workflow.
Use a deeper AI-agent or integrated system.

What you receive

Current-state workflow map and a baseline of time, cost, quality, or friction.
Prioritized opportunities and comparison of alternatives.
Benefit, cost, risk, and feasibility analysis, with assumptions and evidence gaps.
Recommended next action, including a clear no-go when investment is not justified.

Bounded to one team, one workflow family, or approximately two to three candidates. A decision memo may capture the conclusion; this is not a company-wide AI strategy report.

Stage 2 / Make the opportunity implementable

Workflow Design

Specify how people and technology will work together.

For one approved opportunity, define where human judgment is necessary and what happens when the normal path fails.

The operating design

Future-state workflow, inputs, outputs, and handoffs.
Human and AI responsibilities, review gates, exceptions, and escalation paths.
Required data, tools, integrations, and privacy, security, and governance considerations.

The implementation brief

Quality and evaluation criteria, backlog, and acceptance criteria.
Adoption and training plan, with a named workflow owner.
Expected operating cost and a measurement plan tied to the baseline.

Proceed only when expected benefit, feasibility, and organizational readiness justify design. The design can be handed to your team for implementation.

Stage 3 / Put the improvement into use

AI Workflow Deployment Sprint

One usable workflow, beyond a demonstration or slide deck.

Implement the approved design within the agreed scope. Depending on the need, this may involve a configured ChatGPT workspace or another suitable tool, prompts, projects, runbooks, task instructions, or a lightweight automation or integration. Tool choice follows the workflow.

A working system

Configured workflow, structured templates, and reusable operating procedures.
Human review and approval gates.
Evaluation tests and quality checks against agreed acceptance criteria.
Usage, cost, and outcome measurements.

A team ready to own it

User onboarding and training.
Documentation, operating instructions, and exception handling.
Operational handoff to a named owner, including access and recurring costs.
Results compared with the baseline, with limitations and unresolved issues recorded.

Default: one workflow, one team, one measurable objective. If the assessment favors conventional automation or process change, any delivery scope reflects that conclusion.

What you provide

Access to the work
and the people who own it.

A workflow owner and a sponsor able to approve work.
Representative examples, frequency or volume, and baseline information.
Current tools, constraints, desired outcome, and relevant deadline.
Availability for clarification, testing, and adoption.
Agreed, limited access to approved data and systems.

Begin with a non-confidential summary. Data handling and use of AI tools are agreed before customer materials are processed.

Scope and finish

A defined improvement.
A defined handoff.

No indefinite development, embedded staffing, or ongoing managed service is included by default. Support duration, any correction window, and acceptance are agreed in writing.

Additional workflows, integrations, or post-handoff support need a separate scope. A broader engagement may be considered after successful delivery.

Savings and business outcomes are not guaranteed. Fees and schedules are agreed for the actual scope before work starts.

Each stage is a fresh investment decision.

The assessment stands alone. Stage 1 can end with no further work. Stages 2 and 3 proceed only with an approved opportunity, expected benefit, feasible scope, and a team ready to operate it.

See the practical engagement flow →

Good fit

Real work.
An accountable owner.

A recurring workflow and an available workflow owner.
Examples and baseline information the team can share.
A measurable operational outcome.
A sponsor who accepts that the answer may not be AI.
One bounded area in which to begin.

Not a fit

Scope without limits.
Automation without accountability.

AI mainly for appearance or marketing.
No workflow owner or implementation sponsor.
An undefined company-wide transformation.
Fully autonomous operation without human accountability.
Expectations of guaranteed savings or results.
Unrestricted sensitive-data access before a bounded pilot is established.

Start with one recurring problem

Which workflow needs
to work better?

Tell us about work that consumes too much time, produces inconsistent results, or is being considered for AI.