AI integration services
AI integration that writes to your systems of record without breaking them
The model is the small part. The work is reading from and writing to your CRM, ERP, support desk and databases safely, with the right credentials, retries when an API fails, and a log of what changed. We build that layer.
Free 30-min call. No pitch, no slides.
A single focused integration starts in the low four figures.
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Quick answer
AY Automate provides AI integration services: connecting language models and agents to CRMs, ERPs, support tools, databases and internal systems with scoped credentials, error handling, logging and monitoring. Typical timeline: two to six weeks per integration, scoped after the audit call. A single focused integration starts in the low four figures.
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What it is
What AI integration services include
An integration has three jobs. Get the right data to the model at the right moment. Take the model's output and turn it into a valid change in a system of record. And survive the ordinary failures: rate limits, timeouts, schema changes and duplicate events.
We use existing APIs, webhooks and exports where they exist. When an integration touches customer or financial records, writes go through validation and are logged, so a bad output produces a rejected write instead of a corrupt record.
We also put results where people already work. An AI feature inside the existing product gets used. One in a separate dashboard often does not.
Fit check
Is this the right fit?
Where this wins
Sales teams losing hours to research and CRM upkeep
Agents prepare accounts, update records and score leads before the call.
Existing products that need AI features
We add personalization, segmentation or matching inside the live product without a rebuild.
Teams with several disconnected systems
Inquiries, documents or records scattered across tools that need one tracked flow.
When NOT to use this
- The system you want to connect has no API, export or database access. We will tell you what a workaround costs before building.
- You want one more standalone AI tool. Integration is about existing workflows, not new destinations.
- Data cannot leave a boundary and no approved model route exists. We resolve that first.
How it works
How an integration project runs
Read access first, writes second, and nothing writes to production until it has run on samples.
- 01
Systems and access map
Week 1List each system, its API, who owns credentials and what the AI may read and write.
DeliverableIntegration map and access plan
- 02
Read path
Week 1 to 3Pull the right data into the model with the right context, in a sandbox first.
DeliverableWorking read integration
- 03
Write path with validation
Week 3 to 5Turn outputs into valid changes with schema checks, approvals where needed and logging.
DeliverableValidated write integration
- 04
Failure testing
Week 5 to 6Simulate timeouts, duplicates and bad outputs and confirm the system recovers.
DeliverableFailure test results
- 05
Go live and monitor
Release with alerting and a runbook, then review the first weeks of logs.
DeliverableLive integration and monitoring
Typical timeline
Two to six weeks per integration, scoped after the audit call
Stack we build with
n8n · TypeScript · Python · Claude · OpenAI · PostgreSQL · Supabase · Webhooks
Use cases
Integrations we build most
CRM enrichment and updates
Records updated and leads scored automatically from research and call data.
Support desk automation
Requests classified, answered or routed with context attached.
Inquiry to booking tracking
Multilingual inquiries scored and followed up, tracked in one place.
First 30 days
What you have after 30 days
A working read path and a validated write plan, tested on samples.
Week 1
Integration map
Every system, API and credential owner listed, with what the AI may read and write.
Week 2 to 3
Read integration
The right data reaching the model in a sandbox, with the context it needs.
Week 4
Validated writes
Outputs turned into schema-checked changes on sample data, with logging.
Day 30
Failure test report
Timeouts, duplicates and bad outputs simulated, with fixes noted.
Scope
Scope and exclusions
In scope
- Connectors to CRM, ERP, support, database and internal APIs
- Credential scoping, validation of every write and audit logging
- Retries, idempotency and error alerts
- AI steps for extraction, classification, drafting or matching
Not in scope
- Replacing or migrating your CRM or ERP
- Custom development inside vendor platforms that forbid it
- Integrations with systems that offer no programmatic access
- Data warehouse or BI programme build-outs
Results
Results from comparable work
Achieved results only. Clients that have not agreed to be named are described instead.
Agents do pre-call research, update the CRM and score leads automatically. Research time per prospect dropped and the sales team's conversion rate went up.
Two engineers shipped personalization, segmentation and churn prediction inside the live product, and left an architecture that lets new AI features keep shipping without a rebuild.
Inquiries from several countries and languages are now scored and followed up automatically in the right language, with the full journey from inquiry to treatment tracked in one place.
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.
List the systems you want connected
A 30 minute call. We look at your systems and tell you what the integration touches, what can break and what it would take.
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 integration questions
What does an AI integration agency do?+
It connects AI models and agents to the systems your team already runs, so the AI reads live data and writes valid changes back. In practice that means CRM, ERP, support desk and database connectors, scoped credentials, retries when an API fails and a log of every write. The model is the small part of the job.
Is AI integration different from automation integration?+
Automation integration moves data between tools on fixed rules, for example a new deal in the CRM creating an invoice. AI integration adds a model step that reads, classifies or drafts, and its output has to be validated before it touches a record. We build both, often in the same workflow.
Can AI write directly into our CRM or ERP?+
Yes, through validated writes. Every change is checked against the schema and logged, and risky changes can wait for a person. A bad model output becomes a rejected write, not a corrupt record.
Do you use n8n or custom code?+
Both. n8n covers many integrations quickly, see our n8n agency page. Custom code fits tight security or heavy logic. The choice depends on maintenance cost and your team.
What if an API changes or fails?+
Retries, idempotency keys and alerts handle the ordinary failures. Schema changes show up as alerts, and a maintenance plan means someone fixes them.
What does it cost?+
A single focused integration starts in the low four figures. Multi-system builds are scoped after an audit call.
Which models do you use?+
Claude and OpenAI models mostly, chosen per task. Where data cannot leave a boundary, we design around the route your security team approves.