Data pipelines that let agents act on your systems of record
An agent is only as useful as the data it can read and the writes it's trusted to make. We build the governed pipelines between your agents and your ERP, CRM, warehouse, and databases — fast reads, safe writes, full lineage.
- Change data capture & read models
- Idempotent, gated writes
- End-to-end lineage
- Runs in your VPC or on-prem
The gap between a clever agent and a useful one
Demos read a CSV. Production reads your business.
Most agent prototypes work because someone handed them clean, static data. The moment you point one at a real system of record, the hard problems show up: the data is stale, the schema is undocumented, two systems disagree about the same customer, and nobody is sure whether the agent is allowed to change anything.
A data pipeline is the unglamorous layer that closes that gap. It decides where the agent reads from, how fresh that data is, what it's permitted to write, and how every action gets recorded. Get it right and the agent becomes a trustworthy operator. Get it wrong and you've automated your way into a data-integrity incident.
The layers of an agent data pipeline
Each piece exists to make agent access fast, safe, and observable — not just connected.
Ingestion & CDC
Stream changes out of source systems with change data capture instead of brittle batch dumps, so reads stay fresh without hammering production.
Read models & retrieval
Shape source data into query-ready read models and embeddings the agent can scan in milliseconds, including vector indexes for semantic lookup.
Write-back layer
Push agent decisions back through each system's own API or service layer, so validation, permissions, and triggers all still apply.
Idempotency & safety
Request keys, dry-run previews, and reconciliation passes guarantee a retried or duplicated action never corrupts the system of record.
Lineage & observability
Every row, transform, and mutation is traced end to end, so you can answer exactly what the agent changed and why.
In-perimeter execution
Run the whole pipeline inside your VPC or on your own hardware when regulated data can't cross the boundary.
From source map to live pipeline
A measured path that earns write access one stage at a time.
Map the sources
Inventory the systems of record, their schemas, freshness, and the real contracts behind each API or export.
Build read-only
Stand up ingestion, read models, and retrieval first — the agent reads and proposes, but writes nothing yet.
Open writes safely
Introduce idempotent, gated write-back with dry-runs and approvals on the highest-impact mutations.
Reconcile & scale
Run continuous reconciliation against sources, then widen the agent's authority as the lineage proves it correct.
Writes that can't quietly break things
The scariest moment in any agent rollout is the first time it changes a real record. We design for that moment from the start. Mutations are idempotent and carry a request key, so a network retry or a confused re-plan can't post the same refund twice or open a second duplicate case.
High-impact actions run as a dry-run first, surfacing exactly what would change before anything is committed, and can require a human approval. After every batch the pipeline reconciles its writes against the source of truth, so drift is caught in minutes — not in next quarter's audit.
- Idempotent, keyed mutations — no double-posts
- Dry-run previews before any commit
- Approval gates on high-impact writes
- Continuous reconciliation against the source
Direct database access vs. a governed pipeline
Why pointing an agent straight at your tables is a liability, not a shortcut.
| Agent hits the DB directly | Agent through a governed pipeline | |
|---|---|---|
| Reads | Slow scans on production | Fresh read models, no production load |
| Writes | Raw table writes, bypassing logic | Through the system's own API & validation |
| Retries | Risk duplicate or partial changes | Idempotent and keyed — safe to retry |
| Oversight | No record of what changed | Full source-to-write lineage |
| Perimeter | Credentials sprayed everywhere | Scoped access inside your VPC |
Related integration capabilities
Data pipelines rarely ship alone — these are the pieces they connect to.
Frequently asked questions
Do agents read straight from production, or from a copy?
Reads usually run against a near-real-time replica or a read model fed by change data capture, so an agent's scans never add load to the database your business runs on. Writes go back to the system of record through its own API or service layer — never a raw table write — so existing validation and triggers still fire.
How do you keep an agent from corrupting a system of record?
Every write is idempotent and carries a request key, so a retried action can't double-post an invoice or duplicate a ticket. High-impact mutations sit behind approval gates and dry-run previews, and the pipeline reconciles against the source after each batch to catch drift before it compounds.
Can we trace what an agent did and why?
Yes. Every extract, transform, and write is logged with the input record, the model's decision, the tool call, and the resulting change — a full lineage graph from source row to system-of-record mutation. That trail is what makes an agent auditable instead of a black box.
Does this work with legacy systems and on-prem databases?
It does. We connect through whatever the system actually exposes — REST, SOAP, ODBC, flat-file drops, message queues, or a screen-scraped UI when there's no API at all — and run the pipeline inside your VPC or on your own hardware when data can't leave the perimeter.
Give your agents data they can act on.
Bring one system of record and one workflow. We'll map the reads, the safe writes, and the lineage in a single working session.