Custom pipelines that wire agents into your systems of record
An agent is only as trustworthy as the plumbing behind it. We build the integration layer — idempotent, observable, and governed — that lets agents read and write your ERP, CRM, warehouse, and ledgers without ever corrupting them.
- Idempotent, replayable writes
- CDC, queues & event streams
- End-to-end decision lineage
- Approval gates on high-risk steps
Demos call APIs. Production needs a pipeline.
The gap between a working agent demo and a system you'd trust with your general ledger is almost entirely integration.
In a demo, the agent calls an endpoint and something happens. In production, that same call has to survive retries, partial failures, schema drift, rate limits, and a model that occasionally decides to do the wrong thing with total confidence. Hand an agent a write credential and you've built a very expensive way to corrupt your data.
A pipeline is the durable layer in between. It turns messy, fallible agent intent into ordered, idempotent, auditable operations against your systems of record — and gives you a place to put the controls: validation, approvals, throttles, and rollback. The agent proposes; the pipeline is what actually commits.
The integration layer, end to end
Every pipeline is bespoke to your stack, but these are the building blocks we assemble.
Connectors to systems of record
Typed adapters for your ERP, CRM, billing, and warehouse — with the quirks of each handled once, in one place.
Event streams & queues
Change-data-capture, message queues, and ordered event logs so agents react to facts, not stale snapshots.
Idempotent action layer
Keyed, retry-safe operations and state machines so a repeated or failed step never double-applies.
API & schema architecture
Stable contracts, versioned schemas, and an anti-corruption layer that shields agents from upstream drift.
Grounding & retrieval
Vector and structured retrieval so the agent acts on the current state of your data, with citations to source rows.
Lineage & observability
Every payload, decision, and write captured as immutable, replayable lineage for debugging and audit.
From systems map to governed flow
A measured path that earns write access one safeguard at a time.
Map
We inventory your systems of record, their real interfaces, ownership, and the failure modes that actually bite.
Model
We design the typed events, idempotency keys, and contracts the agent will work against — read-only first.
Gate
We add validation, approval checkpoints, and throttles, then enable writes behind those controls in staging.
Operate
We ship to production with lineage, alerting, dead-letter handling, and replay — and widen autonomy as trust builds.
Bridging the legacy systems nobody wants to touch
The systems most worth automating are usually the ones with the worst interfaces — a thirty-year-old ERP, a SOAP endpoint, a nightly flat-file drop, a database you're not allowed to write to directly. Agents can't be trusted to improvise against surfaces like that.
So we build an anti-corruption layer in front of them. The pipeline reads via change-data-capture or scheduled extracts, normalizes everything into clean typed events, and writes back through narrow, validated operations. The brittle edge stays contained; the agent only ever sees a stable, well-described contract.
- CDC, file feeds, SOAP, and RPA fallbacks
- Anti-corruption layer absorbs upstream change
- Narrow, validated write paths only
Direct tool calls vs. a custom pipeline
Why the integration layer is what makes agent autonomy safe to trust.
| Agent calling APIs directly | Agent behind a custom pipeline | |
|---|---|---|
| Repeated actions | Double-posts, duplicate records | Idempotent — keyed and safe to retry |
| Failures | Lost or half-applied writes | Dead-lettered, replayed, or rolled back |
| Upstream change | Breaks silently on schema drift | Absorbed by an anti-corruption layer |
| High-risk steps | Executed immediately | Held for human approval at the gate |
| Auditability | Scattered logs, if any | Immutable, replayable lineage end to end |
Frequently asked questions
Why not just give the agent API keys and let it call our systems directly?
Because raw tool calls have no memory of what already happened. The same prompt run twice can double-post an invoice or re-open a closed ticket. A pipeline sits between the agent and your systems of record to enforce idempotency, ordering, retries, and approval gates — so a retried or hallucinated action can't corrupt the ledger.
How do you connect to legacy systems that have no real API?
We meet them where they are. Change-data-capture off the database, file drops, SOAP and flat-file feeds, screen-level RPA as a last resort — then we normalize all of it into a typed event stream the agent works against. The agent never talks to the brittle edge directly; the pipeline absorbs that surface.
What happens when a write fails halfway through?
Every step is idempotent and keyed, so it can be retried safely. State machines track each unit of work, failed steps land in a dead-letter queue with full context, and compensating actions roll back partial writes. Nothing silently disappears, and nothing gets applied twice.
Can we see exactly what the agent did and why?
Yes. Every decision, tool call, payload, and approval is captured as immutable lineage you can replay end to end. When finance or audit asks why a record changed, you can show the exact event chain — input, model reasoning, the write, and who signed off.
Related capabilities
Pipelines rarely ship alone — these are the pieces they connect to.
Bring the system you're afraid to let an agent write to.
One working session to map your systems of record and design the pipeline that makes autonomous writes safe.