Streaming + batch pipelines01 / 06
Data pipelines
Streaming and batch, with backpressure and replay. Idempotent transforms so reruns never double-count.
Data Science & Engineering
Where did this number
come from? One click.
Streaming and batch pipelines, schema-enforced at the seams, with backpressure, replay and end-to-end lineage — engineered to feed analytics, forecasting and machine learning in production.
Data Science & Engineering
- Streaming + batch pipelines
- End-to-end lineage
- Forecasting in production
What we ship
The data front door, engineered for the worse days.
Every upstream system has its own definition of ‘event’. We make sure they all land in ours, schema-enforced at the seam.
02 / 06
Ingestion at the seam
Streams and batch drops land schema-enforced, with manifest and checksum, for the days upstream has a worse day than we do.
03 / 06
Modern data platforms
Warehouse and lakehouse foundations that analytics, data science and ML teams can all build on.
04 / 06
Lineage you can query
End-to-end lineage, so the question ‘where did this number come from?’ has a one-click answer.
05 / 06
Forecasting
Hierarchical demand forecasting for supply chain and retail — including the long-tail SKUs that break simple models.
06 / 06
Data science to production
Pipeline design, stream processing and the models the data feeds — shipped, monitored and owned, not left in a notebook.
How we work
Filed publicly, so partners know what to expect.
Answer rate is the SLA: a 24-hour reply on every inbound. Not “next sprint.” Not “after discovery.”
- 12
- Active data pipelines
- 99.7%
- Inference uptime · 2025
- 200ms
- p99 latency · production
- 01
We engineer; we don’t deck.
Work shows up as code, infrastructure and shipped systems. Slides arrive late, if at all.
- 02
One SOW. One team.
No subcontractor cascade. The engineers you meet on day one write the code on day ninety.
- 03
We ship our own products first.
Every Labs product was paid for by us before it was sold. We don’t pitch what we haven’t bet on.
- 04
We say so when we’re not the right fit.
If your problem belongs elsewhere — Big-4, offshore, your own team — you’ll hear it on the first call.
Engagement · declassified sample
Client identity protected by NDA. Named references available on request.
Related capabilities
The same engineers behind every capability.
Each capability is staffed by the same studio — not siloed teams handing work over walls.
01
Data & Intelligence
Enterprise data and AI, shipped as intelligence.
02
Platform Implementations
Salesforce, Snowflake, ServiceNow, SAP HANA.
03
Engineering
End-to-end software for systems that must not fail.
Open a file
Bring the problem.
We bring the senior practitioner.