AI INTEGRATION
AI integration services for the unglamorous half of the project. We connect agents to the CRM, ERP, helpdesk, repositories and warehouse you already run - including the authentication, rate limits, retries and error handling that nobody estimates and everybody hits.
What AI integration actually involves
AI integration is the work of connecting an AI system to the software a business already runs, so that it can read real records and take real actions rather than demonstrate on sample data. It covers authentication, permissions, data mapping, rate limits, retries, idempotency, error handling and the audit trail across all of it.
This is where most AI projects lose their schedule. The intelligence works. Then the CRM’s API rate-limits at a level nobody checked, the ERP exposes a field that means something different from what it is named, a legacy system has no API at all, and the sandbox does not behave like production. None of this is interesting, and all of it is the project.
We treat integration as its own discipline with its own estimate, surfaced during the readiness audit rather than discovered in week six. Where a system genuinely cannot be integrated, we say so early and design around it.
You probably need this if you recognize these
- You have something that works in a sandbox and cannot reach production data.
- One critical system is spoken about as “the one nobody touches”.
- The same customer record exists in three systems with three different spellings.
- Integration work keeps being described as “just an API call”.
- A previous automation broke because a rate limit or a token expiry was never handled.
- Access is all-or-nothing, so nobody wants to grant it.
What you get
A system and permission map
What each system holds, what it exposes, and what an agent would be entitled to reach.
Governed credentials
Per-agent, least-privilege access with rotation, isolated so one agent’s compromise is not everyone’s.
A resilient call layer
Rate-limit handling, backoff, retries and idempotency keys, so a repeated call cannot double-charge or duplicate a record.
Data mapping
Field-level mapping and reconciliation between systems that disagree about the same entity.
Bridges for legacy systems
Where an API is missing or unusable, a documented adapter rather than screen-scraping we quietly hope holds.
An audited call trail
Every call an agent makes, with parameters, result and timing, attributable to the run that caused it.
A failure design
What happens when a system is down, slow or lying, defined per integration rather than left to a global retry.
How an integration is built
AI integration and implementation services
Inventory
Systems, owners, interfaces, limits and the entitlements each agent would need.
Self-healed - retried with fallback tool. Human not required.
Probe
We test the real API in a real environment, because documentation is optimistic.
Scope credentials
Least-privilege access per agent, isolated and rotatable, agreed with each system owner.
Build the call layer
Retries, backoff, idempotency and error semantics per integration.
Reconcile
Field mapping and identity resolution across systems that disagree.
Instrument
Every call logged and attributed, with alarms on failure rate and latency.
Agents whose value is mostly integration
CRM Hygiene Agent
Almost entirely an integration and identity resolution problem.
Order & Logistics Agent
Spans order management, carriers and support, which is three integrations wearing one name.
Invoice Matching Agent
Lives or dies on ERP access and the reliability of the call layer.
What we connect to
If it has an API, an agent can use it. If it does not, we build the bridge and tell you honestly what that bridge will cost to maintain.
- CRM
- ERP and finance
- Helpdesk and ticketing
- Code repositories and CI/CD
- Data warehouse
- E-commerce and order management
- Email and calendar
- Identity and access
- Chat
- Legacy internal systems
Platform names are shown as examples of the categories agents connect to. They are not partnerships or endorsements.
How access is controlled
Autonomy boundary
Each agent gets credentials for the systems and operations its job requires, and nothing else. Read and write are separate grants.
Approval gates
Granting an agent write access to a new system is a reviewed decision with a named owner, not a configuration change.
What stays human
Approving new entitlements, and any operation your own change-control process already treats as sensitive.
Logging
Every call recorded with agent, parameters, result and timing, so an unexpected change in a system can be traced to the run that made it.
How the work runs
Typical ranges from our engagement model (doc 04 §5), not a quote.
| Stage | Typical | What happens |
|---|---|---|
| Pilot | 3-10 days audit, then 2-4 weeks | System inventory, real API probing, and a hard estimate on the integrations that will be difficult. |
| Build | 3-8 weeks | Credentials, call layer, mappings, bridges, instrumentation and failure handling. |
| Release | 1-2 weeks | Read-only first, then write access per system as the error rate holds. |
| Managed | ongoing, optional | API changes absorbed, tokens rotated, failure rates watched and alarms tuned. |
What we measure
- Least privilege
- Every agent's entitlements scoped to its job and reviewable (Target)
- Idempotent
- Repeated calls cannot duplicate a record or a charge (Target)
- 100%
- Of system calls logged and attributable to a run (Target)
- Your estimate
- Integration effort quantified during the audit, not discovered mid-build (Yours)
“ Until then these are design targets and engineering commitments, not results.
What this looks like in practice
eCommerce catalog and ads hive
Reference scenario · eCommerce. Catalog enrichment and ad operations across a large SKU count, spanning several systems.
Reference scenario - a composite build illustrating our method. Figures are modeled and the model is shown.
Frequently asked questions
What's the difference between this and agent orchestration?
This connects agents to your systems. Agent orchestration coordinates agents with each other. One is about reaching outward, the other about sequencing internally. A single-agent project often needs only this page; a multi-agent process needs both, and confusing them is how scope gets underestimated.
One of our systems has no API. Is that fatal?
Rarely, but it changes the estimate and you should hear that early. Options include a database-level integration, a file-based exchange, a vendor middleware layer, or a documented adapter. We avoid brittle screen-scraping unless nothing else exists, and if we use it, we say plainly what will break it.
How do you keep credentials safe?
Each agent gets its own least-privilege credentials, isolated from other agents, stored in a secrets manager and rotated on a schedule. Read and write are granted separately. This is deliberately narrower than giving an integration platform a broad service account, which is the pattern that turns one compromise into a company-wide problem.
Will this slow our systems down?
It should not, and we design for that: rate limits are respected rather than discovered, calls are batched where the API supports it, and reads are cached where staleness is acceptable. We measure the load we add and report it, because "the AI project" is an easy thing to blame for unrelated slowness.
Do we need to clean our data first?
Not before starting, but you will find out how bad it is. Identity resolution across systems is part of this work, and where quality is the actual blocker, that becomes data engineering for AI with its own scope so you can see what you are paying for.
Who maintains the integrations afterward?
Either your team, with the documentation and runbooks we hand over, or us under a managed workforce agreement. APIs change and tokens expire, so somebody has to own this. Deciding who before go-live is materially cheaper than deciding after the first outage.
Related services
Agent Orchestration
Coordinating agents with each other.
Data Engineering for AI
Pipelines, embeddings and permissions.
Business Process Automation
The processes these integrations end up carrying.