Production-grade appson Foundry and AIP.
Dataphian designs, builds, and operates production software on top of Foundry, AIP, and modern full-stack infrastructure — the layer between raw enterprise data and the people who have to act on it.
| No. | Property | Value | Remark |
|---|---|---|---|
| 01 | Team | Senior engineers only | No bench, no offshore handoff |
| 02 | Platform | Foundry & AIP native | Ontology, pipelines, Workshop, AIP agents |
| 03 | Stack ownership | Data to UI, one team | Pipelines, services, front end, ops |
| 04 | Engagement | Fixed-scope sprints | 6–16 weeks, shipped to production |
Every engagement ships working software — not a slide deck.
Foundry & AIP applications
Ontology modeling, data pipelines, Workshop apps, and AIP-backed agent workflows built directly on your Foundry instance.
Full-stack product engineering
React/TypeScript front ends, Python and Go services, and cloud infrastructure — designed and shipped by the same team, end to end.
AI agents & automation
LLM-backed agents wired into real operational data and existing systems — production workflows with guardrails, not demos.
Consolidating claims data onto Foundry
Migrated fragmented claims data into a single ontology and shipped a Workshop app that cut manual reconciliation from days to hours.
Foundry · Workshop · PythonReal-time routing agent on AIP
Built an AIP-backed agent that re-routes shipments around network disruptions, wired directly into existing dispatch systems.
AIP · React · GoFull-stack risk-monitoring platform
Designed and shipped a production risk dashboard from data pipeline to front end, replacing a legacy spreadsheet process.
Foundry · TypeScript · PostgresScope
We spend the first two weeks in your ontology and your backlog, not in slides. Scope is fixed before code starts.
Embed
Engineers work inside your repos and your Foundry instance, alongside your team — not through a ticket queue.
Ship
Production code ships incrementally, in one- to two-week sprints, reviewed against real data from day one.
Operate
We stay on for the first operational cycle — on-call, monitoring, and the handoff docs your team actually needs.
Full-stack, one team, no handoffs
We don't split data engineering, backend, and front end across three vendors. The same engineers who model your ontology also ship the interface your operators use — so nothing gets lost in translation.
They didn't just build what we asked for — they found the workflow we actually needed and shipped it in a sprint.
Tell us about the problem, not the tech stack
If you're running on Palantir Foundry, AIP, or just need a full-stack team that ships — we're a good fit for a focused engagement, not an open-ended retainer.