AI implementation services
AI implementation services that get past the pilot and into daily use
Most AI projects stall between a promising demo and something the team relies on. The gap is integration, evaluation, monitoring and ownership. We implement chosen use cases end to end and stay until they run without us in the room.
Free 30-min call. No pitch, no slides.
Focused builds start in the low four figures.
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Quick answer
AY Automate provides AI implementation services: taking a selected AI use case from prototype into production with integrations, evaluation tests, monitoring, governance and ongoing maintenance. Typical timeline: four to eight weeks from a chosen use case to a monitored rollout, scoped after the audit call. Focused builds start in the low four figures.
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What it is
What AI implementation services include
You have picked a use case, or a pilot exists. Implementation means connecting it to the systems where the work happens, testing it against real examples, deciding what a person still approves, and putting monitoring around it.
We measure before we launch. A test set built from your real cases tells us if the system is good enough, and tells you what wrong looks like. Launching without that is guessing.
Adoption is part of the job. We put results inside the tool people already use so nobody has to open a new tab.
Fit check
Is this the right fit?
Where this wins
A pilot that works but nobody uses
We find why it stalled, usually integration or trust, and fix that instead of rebuilding.
A decided use case with no engineering capacity
Your team knows what it wants. We provide senior engineers to build it properly.
Regulated teams that need a human in the loop
Automate tracking and follow-up without automating the decision that needs a professional.
When NOT to use this
- You have not chosen a use case yet. Start with the consulting page, then come back.
- You want a model trained from scratch. We integrate and orchestrate existing models.
- No one on your side can review results. Implementation needs a domain owner.
How it works
How an implementation runs
Build against real cases early. Everything else follows from how the system behaves on them.
- 01
Baseline and access
Week 1Collect real examples, confirm system access and define what good looks like.
DeliverableEvaluation set and success measure
- 02
Integration build
Week 2 to 4Connect the model to your systems and put results where people already work.
DeliverableIntegrated first version
- 03
Evaluate and tune
Week 4 to 5Run the evaluation set, study the failures and tune prompts, tools and guardrails.
DeliverableEvaluation report
- 04
Controlled rollout
Week 5 to 8Release to a small group, watch usage and errors, then widen.
DeliverableLive system with monitoring
- 05
Handoff or operate
Your team owns it with a runbook, or we operate it under a maintenance plan.
DeliverableRunbook and support agreement
Typical timeline
Four to eight weeks from a chosen use case to a monitored rollout, scoped after the audit call
Stack we build with
Claude · OpenAI · Python · TypeScript · PostgreSQL · Supabase · n8n
Use cases
What we implement
Patient or customer chatbots in production
Bilingual assistants running alongside operational tracking.
Meeting to text to filed record
Recordings transcribed, documents read and filed, updates routed to the right person.
Inbound support at scale
An agent handling most requests around the clock, escalating the rest.
First 30 days
What you have after 30 days
A measured first version, not a slide about one.
Week 1
Evaluation set
Real examples from your work with the answers you consider correct.
Week 2 to 3
Integrated first version
Running inside the tool people already use, on sample or sandbox data.
Week 4
Evaluation report
Where it is right, where it fails and what we changed because of it.
Day 30
Rollout plan
Pilot group, monitoring and the approval steps agreed before release.
Scope
Scope and exclusions
In scope
- Integration with the systems where the work happens
- An evaluation set built from your real cases
- Human approval steps where judgment matters
- Monitoring, alerts and a runbook
- Handoff or a maintenance plan
Not in scope
- Choosing the business case for you, which is the consulting engagement
- Training foundation models
- Clinical, legal or financial decisions, which stay with your professionals
- Hardware or on-premise GPU procurement
Results
Results from comparable work
Achieved results only. Clients that have not agreed to be named are described instead.
About 120 patients on implantable heart monitors moved from several disconnected spreadsheets into one operational cockpit. Tracking and follow-up are automated without automating the medical decision, and a bilingual patient chatbot runs in production alongside it.
A multilingual WhatsApp AI agent now handles 80% of requests without a human touching them. Response time had averaged over 4 hours. The client reports roughly $18,000 a year saved and support workload down 40%.
Meetings are recorded and turned into text automatically, documents are read and filed without re-typing, and client updates reach the right notary the moment they happen.
Pricing
How this is priced
We do not sell fixed packages sight unseen. The number depends on how many systems the work touches, and the audit call tells you that number before you commit to anything.
Single workflow
Low four figures
One focused workflow set up in hours, with error handling, retries and monitoring built in from day one.
Full system
Scoped after an audit call
AI steps, monitoring and integrations across several systems, typically four to eight weeks. No template price, because scope drives the cost.
Embedded engineer
From $3K/month
A dedicated engineer building and maintaining the work inside your team, instead of a scoped project.
Free 30-min call. No pitch, no slides.
Free automation audit
Find what to automate first, and how AI sees you
We read your homepage, detect your tools, and check your Google rankings and AI Overview. You get a score out of 100. Add a work email to unlock automation opportunities matched to your stack.
Use Claude Code, Cursor or Codex? Paste this into your agent
Fetch https://www.ayautomate.com/SKILL.md and follow it: read my repo or website, pick the 2 to 3 manual loops worth automating first, and give me the booking link.
Tell us about the pilot or use case
A 30 minute call. We look at what exists, what is blocking it and what it would take to run in production.
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
“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
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FAQ
AI implementation questions
How is implementation different from consulting?+
Consulting decides what to build. Implementation builds a decided use case and puts it into production. Many clients do both with us, but you can start at either.
How do you know the AI is good enough to launch?+
We build an evaluation set from your real cases before launch and score the system against it. You see the failures, not just the average.
Can we keep a human approving the results?+
Yes, and often you should. We automate tracking, drafting and follow-up and leave the decision that needs professional judgment with your people.
What does it cost?+
Focused builds start in the low four figures. Larger systems across several tools are scoped after an audit call, typically four to eight weeks of work.
What if our pilot was built by someone else?+
We review it, keep what works and rebuild only what does not. Most stalled pilots need integration and monitoring, not a restart.