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Enterprise AI consulting
Enterprise AI consulting that ends in a system in production
Large organizations rarely lack AI ideas. They lack the map of which ones are worth building, the access and governance to run them, and an engineer who ships the first one. We do the mapping and stay to build.
- Use case mapping
- Governance built in
- Engineers who ship
Trusted by teams at
What enterprise AI consulting includes here
Consulting that stops at a roadmap leaves the hard part undone. Our engagements cover four things in order: finding the use cases worth building, deciding what data and systems the AI may touch, setting the controls for access, logging and approvals, and delivering the first system into production.
That first system matters more than the deck. It shows security what the controls look like in practice, gives the business a real result and gives other teams a reference to copy.
We work alongside your engineering, security and legal teams, not around them. For AI adoption inside a large distributed engineering organization, we have advised leadership and embedded an engineer to prove the pattern in a live team.
Where this wins
Organizations with many AI ideas and no priority order
A mapping exercise turns a long list into a short, ranked one before money is spent.
Regulated or security-sensitive teams
Access scoping, audit logging and approval steps designed before any agent touches real data.
Leadership that needs a first result, not a pilot graveyard
One narrow system in production that others can follow.
When NOT to use this
- · You want a strategy document only. We can advise, but our value is in what ships afterwards.
- · You need a certification or audit attestation from us. We build controls your auditors can review and do not claim certifications we cannot show.
- · You want an enterprise-wide rollout in one step. We start with one system and expand where it sticks.
How an enterprise engagement runs
Map first, build one thing, then expand. Each stage has a deliverable your stakeholders can review.
01
Opportunity mapping
Week 1 to 3Interview teams, list the candidate use cases and rank them by value, risk and effort.
DeliverableRanked opportunity map
02
Governance and access design
Week 2 to 4Decide what data the AI may read, what it may change and who approves what.
DeliverableAccess and control model
03
First system build
Week 4 to 10Build the top-ranked use case with logging, permissions and approval steps in place.
DeliverableWorking system in a test environment
04
Production release
Release with monitoring and a runbook, and review the first weeks of real use.
DeliverableLive system and review
05
Expansion plan
Decide the next systems based on what the first one showed.
DeliverableNext-phase backlog
Typical timeline
Mapping first, then one production system, scoped after discovery
Stack we build with
Claude · OpenAI · TypeScript · Python · PostgreSQL · MCP · n8n · Your cloud account
Not sure which use case comes first?
We map candidates against value, risk and effort and recommend one to build. The audit call is free.
Where enterprise teams start
Role-specific AI skills
Narrow assistants for named roles, deployed with usage tracked in one console.
Governed access to internal data
Agents that see only what each person is allowed to see.
Document-heavy back office
Documents read, matched and routed with exceptions sent to a person.
What your first 30 days look like
A ranked map and a control model you can take to security.
Week 1
Stakeholder interviews
The teams closest to the work describe where time and errors go.
Week 2 to 3
Ranked opportunity map
Candidates scored for value, risk and effort, with a recommended first build.
Week 3 to 4
Access and control model
What the AI may read and change, who approves, and what gets logged.
Day 30
Build plan
A scoped plan for the first system with named owners on your side.
Scope and exclusions
In scope
- · AI opportunity mapping and ranking against effort and value
- · Data access, permission and logging design
- · Security and data-handling review with your teams
- · Delivery of the first production system
- · Handover, monitoring and a plan for the second and third systems
Not in scope
- · Vendor certifications or compliance attestations on your behalf
- · Enterprise-wide change management programmes
- · Replacing core enterprise platforms
- · Guaranteed savings figures before a system has run
Results from comparable engagements
Achieved results only. Clients that have not agreed to be named are described instead.
Sage, business software
Leadership was advised on the AI rollout approach, and one embedded engineer proved the pattern in a live team, which became the reference other teams followed.
Gepromed, MedTech
47 AI opportunities mapped before anything was built, narrowed to 16 deployed role-specific AI skills, with daily usage brought together in one operating console.
AmbryHill, aerospace ERP under FAA, ITAR and AS9100
The whole database became an agent anyone can talk to, with each person seeing and generating reports only for what they are allowed to touch.
How this is priced
Priced per project and scoped after a short discovery call, not sold as a fixed package. Cost follows the number of systems, the access model and the security requirements.
Scoped build
Scoped after a discovery call
Most engagements start with one narrow, high-value piece so you see it running in production before anything expands.
Embedded engineer
From $60,000/year
A dedicated engineer building and maintaining the work inside your team, instead of a scoped project.
Start with one governed system
Book a free audit call. Bring the constraints your security and legal teams care about, and we plan around them.
Book a free audit callBook a free audit call
Tell us where AI should start
A 30 minute call. We look at your teams, systems and constraints and recommend which first use case would earn trust.
Book a 30min Free Strategy Call
In this call, we'll walk through your project scope, timeline, and goals - so we can both check if we're a fit. No obligation, no slide deck, just a working session.
Don't want a call? Email walid@ayautomate.com
Opportunity Map
Implementation Path
Fast Follow-Up
“The team is super fast - sometimes we had to slow them down. We managed to scale the company without investing into hiring.”
Elie Salame
COO, Adstronaut.io
Video Call
Phone Call
In-Person
We've created products featured in
Walid Boulanouar
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This call is for teams ready to move. If that's you, pick a time.
30min
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Usually responds in 1 hour
No commitment required
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FAQ
Enterprise AI consulting questions
How is this different from a strategy consultancy?+
We build. The output of the mapping phase is a system in production, not only a report. Engineers who write the code take part in the scoping, so the plan reflects what can be built.
Do you handle security and compliance?+
We design access controls, logging and approval steps and review data handling with your security team. We do not claim certifications we cannot show, and your auditors have the final say.
How long before something is in production?+
We map first, then ship one production system. Timing depends on integrations and review cycles, and we scope it after discovery.
What does it cost?+
Scoped after a discovery call because it depends on systems, access model and security requirements. Placement of an embedded engineer starts from $60,000/year.
Can you work with our existing teams and vendors?+
Yes. We work alongside your engineering and security teams and connect to the tools you already run.