“Where could AI help us?”
Begin with an opportunity assessment: process friction, available information, feasibility and a prioritized use-case shortlist.
Assess the opportunity ↗START WITH THE DECISION
Where are you
with AI today?
Choose the question you need to answer. The next step should reduce uncertainty, not add another tool.
“Will this idea actually work?”
Define a bounded pilot with representative examples, failure cases and acceptance criteria before committing to wider implementation.
Design a fair test ↗“How do we operate it responsibly?”
Plan integrations, permissions, monitoring, escalation and the people responsible for the workflow after release.
Prepare for real use ↗01 / DEFINE THE BUSINESS CASE
Find the right opportunity
Choose a useful problem and establish the conditions for a fair test.
01
AI opportunity assessment
Find where AI can remove friction in a measurable business process.
What we do
- Map the workflow, task volumes, handoffs, exceptions and the cost of the current approach.
- Compare AI with simpler alternatives such as rules, integrations or process changes.
- Prioritize opportunities by potential value, feasibility, risk and available evidence.
What you receive
A use-case shortlist, process map, assumptions and a recommended first project with success measures.
Good starting points include document intake, internal knowledge lookup and human-reviewed response drafting. Savings estimates are assumptions to test, not guaranteed returns.
02
Data & knowledge readiness
Understand whether the information can support the proposed workflow.
What we do
- Identify source systems, content owners, update frequency and access permissions.
- Review a representative sample for completeness, accuracy, format and sensitive information.
- Define source-of-truth, retrieval boundaries and an approach to keeping information current.
What you receive
A data readiness review, source inventory, access requirements and a gap-resolution plan.
You remain responsible for approving data use and confirming rights and permissions. Avoid moving production data into an unapproved tool during discovery.
02 / TEST BEFORE YOU SCALE
Design a controlled pilot
Build a limited, reviewable workflow with a clear way to judge its output.
03
Pilot design & evaluation
Replace a convincing demo with a test your team can assess.
What we do
- Define the task, representative test cases, expected outputs and unacceptable failure modes.
- Set acceptance criteria for quality, groundedness, latency, cost and human review as appropriate.
- Compare a baseline approach with the proposed solution and document failure cases.
What you receive
A pilot specification, evaluation set, acceptance criteria and a findings report supporting a continue, revise or stop decision.
Evaluation uses examples appropriate to the business. A successful pilot does not by itself prove production readiness.
04
Assistants, agents & workflow automation
Give the system a defined task and bounded permissions.
What we do
- Design knowledge assistants, drafting tools or task workflows around approved use cases.
- Separate suggestions from actions; define when a person approves, edits or takes over.
- Specify allowed tools, input checks, escalation paths and recovery from unexpected results.
What you receive
A scoped workflow design or prototype, tool-permission map and human-review rules.
The design determines the appropriate level of automation. We do not assume that every workflow should act autonomously.
03 / CONNECT & GOVERN
Prepare for real operations
Plan the system connections, safeguards and ownership needed beyond a demonstration.
05
Integration & architecture planning
Fit the workflow into the systems your team relies on.
What we do
- Review available APIs, authentication, data flows and constraints in your CRM, ERP or business applications.
- Define record mapping, validation, retries, duplicate handling and the system of record.
- Compare model and hosting options against your data requirements, operating costs and support needs.
What you receive
An architecture outline, integration specification, dependency list and delivery estimate assumptions.
Third-party API access, licensing and platform terms need verification before committing to implementation.
06
Governance, rollout & operating model
Make responsibilities and controls explicit before wider use.
What we do
- Document data handling, access, logging, retention and approval requirements for the agreed workflow.
- Plan user training, monitoring, feedback collection and escalation when output quality changes.
- Define release gates, owners and what ongoing support would cover.
What you receive
A rollout checklist, responsibility map, monitoring requirements and a proposed improvement backlog.
Legal or regulatory requirements should be confirmed with your qualified advisers. The consulting scope does not imply a compliance certification.
FROM PRIORITIES TO DELIVERY
A clear process.
A shared definition of success.
- 01
Understand
Review the business process, current baseline and decision the project needs to support.
- 02
Specify
Agree data boundaries, delivery scope, risks and acceptance criteria.
- 03
Evaluate
Run a focused prototype or pilot against representative examples and record the limitations.
- 04
Decide
Review the evidence and agree whether to refine, stop or scope production delivery.
We assess useful output quality, exception rates, review effort, latency and operating cost against the current baseline. The relevant measures depend on the use case. Business benefit is validated with your team rather than inferred from a model benchmark.
WHAT A USEFUL EVALUATION CHECKS
A good answer is only
one part of the test.
Agree the evaluation dimensions before the pilot. The thresholds should reflect the task, the consequences of a mistake and the current manual baseline.
- Correctness & grounding
- Does the output answer the question accurately, use permitted sources and identify when it lacks evidence?
- Exceptions & escalation
- What happens with missing data, conflicting sources, unusual requests or attempts to override the workflow’s instructions?
- Human review effort
- How often does a reviewer need to correct, reject or investigate the output? Compare the total workflow effort, not just generation speed.
- Cost & response time
- Assess model usage, retrieval, integrations and review overhead under representative task volumes.
- Access & action boundaries
- Check which records can be read, which tools can be used and which actions need explicit approval.
The pilot ends with a decision.
Continue with a scoped rollout, revise and retest, or stop when the evidence does not justify the investment. Each is a valid outcome.
CLEAR SCOPE. CLEAR OWNERSHIP.
Know who does what.
These are the responsibilities we clarify together. The proposal confirms exact deliverables, approvals and dependencies.
| Workstream | Our role within scope | Your team’s role |
|---|---|---|
| Business case | Facilitate discovery and compare delivery options. | Provide process context, priorities and baseline information. |
| Data & permissions | Identify technical requirements and recommend boundaries. | Approve sources, access, retention and permitted use. |
| Evaluation | Prepare the agreed test approach and document findings. | Supply representative examples and judge domain correctness. |
| Integration & rollout | Design or implement the separately agreed connections and controls. | Provide system owners, access approvals and user acceptance. |
| Ongoing operation | Define monitoring and support options within scope. | Assign process owners and escalation decision-makers. |
WHAT DELIVERY CAN LOOK LIKE
A practical starting roadmap.
Illustrative sequence, not a promised timeline or package inclusion. Discovery and your priorities shape the actual plan.
Discovery decision
Assess one workflow, its data and the current baseline.
Example output: Use-case brief, feasibility findings and open questions.
Pilot decision
Test a limited workflow against agreed examples.
Example output: Evaluation results, failure cases and a recommendation.
Production decision
Confirm controls, dependencies, ownership and rollout requirements.
Example output: A scoped delivery plan and release acceptance checklist.
BEFORE WE BEGIN
Your questions, answered.
Do we need to know which AI model to use?
No. Begin with the task, data constraints and acceptance criteria. Model choice follows those requirements and may change after testing.
Can we start without sharing sensitive data?
Often, discovery can begin with process descriptions and synthetic or redacted examples. Any later use of sensitive data requires an agreed, approved environment.
Is a prototype included in every engagement?
No. Assessment, pilot development, production implementation and support are distinct scopes. Your proposal states the deliverables and boundaries.
Can you connect AI to our existing systems?
We assess the available APIs, permissions and system constraints first. Integration work is estimated after the required connections and behavior are defined.
How do you prevent incorrect answers or actions?
No AI system is error-free. We define test cases, source boundaries, validation, review steps and escalation for the use case. High-impact actions require appropriate human approval.
How are costs agreed?
Scope, data readiness, integrations, evaluation and rollout needs determine the estimate. Model usage, hosting, licenses and support costs are identified separately.
YOUR NEXT STEP
Let’s find a useful
first AI project.
Tell us where your team loses time, what systems are involved and what a better result would look like. We’ll discuss a sensible starting scope.
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