Zero-Integration Partnerships: Agents that auto-generate, validate, and maintain APIs between businesses

Traditional B2B partnering dies on integration: weeks or months of mapping fields, haggling over payloads, and fixing breakages every time someone changes a field name. In supply chains and finance, onboarding a trading partner often takes a week to a month - or longer. The market has tried EDI networks, unified APIs, and prebuilt connectors to reduce that burden, but they still leave you with coordination costs and drift. The question is: can agents generate, verify, and maintain the API boundary for us - so "integration" becomes a no-meeting handshake? (Cleo, eliassen.com)

The idea in one line

Agents take a mission ("exchange orders, invoices, statuses"), learn each side's systems, propose a shared contract (OpenAPI for request/response, AsyncAPI for events), compile adapters, prove compatibility with contract tests, and watch for drift - re-generating mappings and specs when either side changes. Concepts like unified APIs show the value of normalizing across providers; the leap here is to have agents generate that normalization per-partner, on demand. (Merge)

Why this matters now

• Standards are mature. We have common, machine-readable formats to describe synchronous and event-driven interfaces (OpenAPI, JSON Schema, AsyncAPI) and linters to enforce quality (Spectral). (asyncapi.com, stoplight.io)
• Contract testing exists. Consumer-driven contracts (e.g., Pact and bi-directional variants) let us assert compatibility between producer and consumer without full end-to-end staging. Agents can own this loop. (docs.pact.io, docs.pactflow.io)
• Industry rails exist. Networks like Peppol and GS1 EDI already encode business documents and identifiers; agents can compile to these rails when the use case fits. (The Invoicing Hub, peppol.com, GS1)

Reference architecture

flowchart LR
  A[Partner Discovery] --> B[Schema & Event Learning]
  B --> C[Contract Synthesizer (OpenAPI / AsyncAPI)]
  C --> D[Adapter Compiler (mappings, auth, transforms)]
  D --> E[Contract Tests (Pact + Mock Provider)]
  E --> F[Drift Watcher (schemas, payloads, SLAs)]
  F --> C
  E --> G[Readiness Gate]
  G --> H[Prod Exchange]
  H --> I[Evidence Ledger (traces, costs, decisions)]

Flow: ingest sample payloads and docs → infer entities and events → propose contracts → compile adapters (validation, mapping, auth) → run contract tests → gate release → monitor drift and re-synthesize as needed. Everything is logged to an evidence ledger for audit and debugging. (docs.pact.io, stoplight.io)

Operating model (end-to-end)

1) Partner discovery and learning

Agents crawl partner docs, sample payloads, and metadata. They infer entities, constraints, and events, then assemble a draft OpenAPI spec for requests and an AsyncAPI spec for subscriptions/notifications. They attach JSON Schemas and example payloads gathered from sandbox traffic. (asyncapi.com)

2) Contract synthesis with quality rules

Draft contracts are linted with Spectral and local style guides. The agent explains any ambiguous fields and proposes canonical names and datatypes. Output is a PR: openapi.yaml, asyncapi.yaml, and a typed model package. (stoplight.io, GitHub)

3) Adapter compilation

For each side, the agent compiles adapters that:

• Transform internal fields to the shared contract (and back).
• Authenticate using the partner's preferred mechanism.
• Validate bodies against JSON Schema before send/accept.
• Normalize enums, time zones, currencies, and IDs (GLN/GTIN when relevant). (GS1)

4) Proof via contract tests

The agent generates consumer-driven contract tests (Pact) and, if permitted, spins a mock provider to validate the surface. Partners can also publish their capability contracts (bi-directional testing) to check compatibility without a joint staging window. Gate production on all tests passing. (docs.pact.io, docs.pactflow.io)

5) Drift watch and self-maintenance

Once live, a watcher compares observed payloads and specs for divergence: new fields, changed enums, breaking renames, SLA slippage. When it detects drift, it: raises a PR with the new contract diff, regenerates adapters/tests, and requests approval. Think of it as CI/CD for partnerships. (stoplight.io)

Reliability and governance

Decision rights and gates

You keep control by placing human gates on: contract approval, auth scope, rate limits, and any mapping that touches regulated fields. No agent merges its own PRs to production branches.

Guardrails

• Input: policy and PII filters; only approved data sources.
• Output: schema validation and Spectral rules; deny on breaking changes.
• Eventing: only topics declared in AsyncAPI get published/consumed. (asyncapi.com)

Cost ceilings

Set spend caps for discovery, mock traffic, and egress. Alert at 80%; trip at 100%. This matters when agents enumerate large partner catalogs or hydrate sandboxes.

Evidence ledger

Every action - generated spec, lint results, contract test run, approval - lands in an immutable log associated with the partner and version. This makes audits and post-mortems routine.

Interop with existing rails

This approach doesn't reject EDI/Peppol; it compiles to them when appropriate. If a trading partner insists on Peppol BIS for e-invoices, the agent maps to those profiles and uses the network's "connect once" model. If a retail partner uses GS1 identifiers, mappings preserve GLN/GTIN/SSCC. The value is removing handcrafting and keeping contracts synchronized over time. (The Invoicing Hub, ClearTax, GS1)

KPIs that prove it works

• Time to first data: hours or days, not weeks. Baseline: many EDI onboardings still span 1–4+ weeks. (Cleo)
• Contract confidence: % of payloads validating cleanly over rolling windows.
• Change lead time: minutes from detected drift to approved adapter update.
• Breakage rate: failed exchanges per 1,000 calls/events after release.
• Human effort: reviewer minutes per new partner.

30-day pilot plan

Week 1 - Frame & discover. Choose one partner and one document set (e.g., orders + fulfilment). Run discovery and produce draft OpenAPI/AsyncAPI with Spectral lint reports and example payloads. Gate on a human review. (stoplight.io)

Week 2 - Compile & test. Generate adapters on both sides. Stand up Pact tests plus a mock provider. Prove round-trip transforms and schema validation with sample data. (docs.pact.io)

Week 3 - Canary & watch. Exchange a low volume of live messages. Enable drift watcher. Track KPIs: validation rate, change lead time, breakage rate.

Week 4 - Harden & decide. Expand traffic, finalize runbooks, and compare onboarding time and defects against your current process. If the deltas are real, template the flow for the next partner.

What this replaces - and what it doesn't

Agents won't replace commercial trust or legal agreements. You'll still need DPAs, SLAs, and human approvals. What they can replace is the manual glue: hand-mapping fields, writing one-off connectors, chasing changes, and spending weeks in coordination. With mature contracts (OpenAPI/AsyncAPI), linters, and contract testing, "zero-integration" becomes feasible: partners exchange business value sooner, and integrations stop breaking quietly. (asyncapi.com, stoplight.io, docs.pact.io)