01
Schema definition
The events and fields each system emits and accepts, versioned and documented before any connector is written.
INTEGRATIONS AND DATA
One version of the truth, moved reliably
Connecting systems that were never meant to talk, with event schemas, idempotent writes, retries and reconciliation you can read.
Trace one broken handoff
30 minutes with an engineer, no sales call
What this is
Data that agrees across every system
Integration work starts with the shape of the data, not the connector. We define the events each system emits and consumes, make every write safe to repeat, handle the failures that will happen anyway, and produce a reconciliation report that shows both sides matching. When a record goes missing, you can see where it stopped instead of comparing exports by hand.
This is for you if
- Two systems hold the same customer or order, and your team decides which one to believe case by case.
- A nightly job moves data, and nobody finds out it failed until someone asks about a missing record.
- Finance and operations report different numbers for the same month and the difference takes days to explain.
This is not the right fit if you run one system and have no reporting requirement across others. There is nothing to reconcile, and adding a pipeline would create a moving part that only needs maintenance.
Scope
What we build
02
Connectors
Adapters for each system that translate to the shared schema, so a change in one vendor does not spread across the rest.
03
Queue or pipeline
A durable path between systems with ordering rules and idempotent writes, so a repeated message cannot duplicate a record.
04
Retry and dead letter handling
Failed messages retried with backoff, then parked with the payload and the reason, ready to replay after a fix.
05
Reconciliation reports
Scheduled comparisons between source and destination that name the records that differ, not just a count.
06
Monitoring on freshness
Alerts on data age and queue depth, so a stalled pipeline surfaces as an alert rather than a question in a meeting.
How it goes
From disagreeing systems to one record
- 01
Flow and field audit
One week
We follow the records that matter through every system, list the fields in conflict and mark the system of record for each.
- 02
Schema and contract
One to two weeks
Event schemas, versioning rules and the write contract per system, agreed in writing with the people who own each side.
- 03
Pipeline build
Three to six weeks
Connectors, the queue, idempotent writes, retries, dead letter handling and the first reconciliation report on real data.
- 04
Monitoring and handover
One to two weeks
Freshness alerts, replay procedure, runbooks and a walkthrough with whoever will be on call for it.
Artefacts
What you receive
Written record
Data flow map across systems
Versioned event schema documents
System of record decision per field
Replay and backfill procedure
The system
Source code in your own repository
Connectors and schema definitions under version control
Idempotent write paths with tests
Dead letter store with payload and reason
Operations
Scheduled reconciliation reports
Freshness and queue depth alerts
Runbook for a failed or stalled run
Handover session recording
Pipelines run inside your own cloud account and credentials stay in your secret store. We never hold sole access.
Related work
The rest of this line
Custom platforms
Web platforms and internal tools built around how your business actually works.
AI assistants and agents
Assistants that answer with your own data and agents that finish real tasks.
Back up one level
Software development
Custom platforms, AI assistants and the integrations that hold them together.
APIs, event pipelines and one reliable version of your operational data.
Questions
Questions we get about integrations and data
Next step
Pick the handoff that breaks most often
Book a technical assessment
30 minutes with an engineer, no sales call