Quick answer
AI integration services connect a model or AI application to the systems where your business works. A useful scope names the records it can read, the changes it can propose, who authorizes those changes, and how the team proves they happened. Buy a complete path from a real input to a confirmed business outcome, including what happens when a step fails.
Scope one transaction before counting connectors
Consider a supplier-onboarding request arriving by email with an attached form. The proposed system extracts details, checks the vendor register, prepares a draft record, and routes it to procurement. That is an illustrative design, not a customer case study. It is useful because every step has a different authority boundary.
Reading an email does not authorize creating a vendor. Matching a supplier name does not establish which legal entity it represents. Creating a draft does not authorize approving bank details. A proposal that says only ‘connect email to the ERP’ leaves those decisions unpriced and unresolved.
Read the request
Retrieve only the approved inbox and records.
Prepare a proposal
Show extracted fields, source evidence, and unresolved matches.
Apply an approved change
Validate the current record, write permitted fields, confirm the result.
A model can help interpret the request. Application code enforces access, validation, and the approval required for a write.
Ask for a contract for each system boundary
A connector name tells you little about the work. The same CRM may expose different fields, permissions, limits, and custom objects in two companies. Ask the provider to verify the actual access path with your system owner before treating an integration as fixed scope.
Use this worksheet to compare proposals. An answer such as ‘handled by the platform’ is incomplete until it identifies the behavior, the responsible team, and a test you can observe.
| Boundary | Write into the scope | Evidence to request |
|---|---|---|
| Read access | Identity, allowed records and fields, freshness requirement | An allowed record succeeds; a forbidden record is denied |
| Input contract | Required fields, identifiers, attachment formats, missing-data path | A malformed or ambiguous request enters a visible exception queue |
| Proposed change | Editable fields, source references, validation rules | A reviewer can inspect exactly what will change |
| Write access | Approver, permitted operation, duplicate protection, record-version check | An expired approval or changed record cannot silently proceed |
| Completion | Destination receipt or authoritative read-back | The case is complete only after the destination confirms the effect |
| Recovery | Retry limits, reconciliation path, operator and response ownership | A failed dependency leaves an actionable case, not a disappearing error |
The expensive failure: a write with no answer
Suppose the vendor system accepts a create request, but the response is lost. The integration now knows it sent a request; it does not know whether the vendor was created. Retrying with a new request can create a duplicate. Marking the case failed can also be wrong.
Ask whether the destination supports an idempotency key: a stable identifier reused for the same intended operation. AWS describes this pattern for preventing duplicate effects when requests are repeated. The provider must verify the destination’s actual contract, including how long keys remain valid and what happens if the payload changes.
If the destination has no equivalent guarantee, require a documented reconciliation procedure. That might use a unique external reference and a lookup, with ambiguous cases held for an operator. A lookup alone does not eliminate a race between concurrent writers. The scope should say which component prevents competing submissions and what happens when the outcome still cannot be established.
Rehearse the awkward cases before accepting the work
A successful demonstration should show the destination state and the operator’s next action, not just a plausible model response. Run these cases against representative test records with the people who will handle exceptions. Set case-specific acceptance criteria before the provider runs the demonstration.
| Test case | Required observable behavior |
|---|---|
| Same request delivered twice | One intended change; both deliveries point to the same tracked operation |
| Write succeeds but response times out | Reuse the destination’s supported operation key or reconcile the result; no untracked repeat write |
| Two suppliers have similar names | No guessed identity; the ambiguity is presented for resolution |
| Record changes after approval | The old approval cannot authorize an unseen change |
| Source access is revoked | The request is denied without exposing cached restricted content |
| A dependency stays unavailable | Retries stop at an agreed limit and a named operator receives the case |
Price the operating boundary as well as the build
Name the hosting account, credential owner, deployment process, and support owner. Customer-owned infrastructure and external model processing are separate questions: document which data is sent to each approved service, how it is retained, and which configurations apply. Do not accept ‘private deployment’ as a complete data-flow description.
Separate the build estimate from platform subscriptions, model usage, internal review time, and ongoing maintenance. Ask who handles an upstream API change, rotates credentials, reconciles stuck cases, and restores service. A handover should include access you control, a runbook, test fixtures, and a working pause procedure.
In the supplier example, acceptance means procurement can resolve an uncertain match, see whether a record was created, and safely resume a stopped request. Those are specific outcomes you can put in a contract and demonstrate before expanding the workflow.
Take this into the conversation
A brief your team can use.
An editable Markdown worksheet for your system owner and prospective delivery team.
Download the integration project briefCommon questions
What if a legacy system has no usable API?
Assess supported file exchange, an approved middleware interface, or controlled user-interface automation with the system owner. Each has different latency and recovery limits. Do not assume direct database writes are supported, or that UI automation will survive every screen change. Price a feasibility check before promising a production integration.
When does this need AI?
If the input and routing rules are already structured, an ordinary integration may be enough. AI becomes a candidate when interpreting variable documents or language is part of the work. Keep calculations, permissions, and business rules deterministic where they can be defined explicitly.
Sources & further reading
Primary documentation for the technical points cited above. The decision frameworks and illustrative examples are PlatformBridge’s editorial guidance.