Mission-critical systems for sectors where downtime has physical consequences.
We engineer in industries where software failure shows up as missed shipments, paused production lines, mistimed broadcasts, or unreconciled ledgers. That gravity shapes how we design, what we measure, and the operational standard we hold ourselves to.
Industrial Supply Chain
Plant-floor telemetry ingestion, ERP integration meshes, warehouse orchestration layers, and supplier-network APIs. We design for high-cardinality time-series data, intermittent edge connectivity, and the reality that downtime in this sector measures in physical inventory, not user sessions.
Media Enterprise Systems
Rights management, asset pipelines, transcoding fleets, and audience analytics for broadcasters and streaming operators. Our pipelines handle petabyte-scale catalogs, frame-accurate metadata, and the long-tail bursts that come with live events and breaking news.
FinTech Platforms
Payments orchestration, ledgering, reconciliation engines, and KYC/AML data flows engineered under regulatory scrutiny. We model invariants explicitly, use append-only data stores where auditability demands it, and treat correctness as a non-negotiable first principle.
Healthcare Data Networks
HL7/FHIR integration, consent-driven data exchange, and analytics platforms that respect patient privacy boundaries. Systems are designed for auditability and provenance: every read and write is traceable to a policy decision, a consent record, and a verifiable actor.
Logistics & Mobility
Routing engines, fleet telemetry, ETA prediction services, and shipper-carrier integration APIs. Our systems remain accurate as networks degrade, traffic shifts, and partner integrations change shape — failure modes that destroy lesser pipelines pass through ours as observable, recoverable signals.
Energy & Utilities
Grid telemetry ingestion, demand-response orchestration, and asset-management platforms for utilities and renewables operators. We build systems that gracefully degrade during weather events and absorb the regulatory reporting requirements specific to each operating jurisdiction.
Different industries, repeatable engineering posture.
The data shapes change. The regulators change. The downstream consequences change. The engineering discipline does not. Across every sector we ship the same three constants: explicit invariants, observable interfaces, and operational hand-offs that outlive the original team.
- Domain models authored by engineers who interview operators, not just product owners.
- Contracts versioned, deprecated, and migrated with the same rigor as database schemas.
- Every regulated boundary mapped to a service boundary, a data store, and an audit trail.
- Runbooks written by the engineers who will get paged when the system misbehaves.
Sector-tuned, but rooted in a single platform vocabulary.
1// industrial :: telemetry ingest2edge.collector → mqtt(qos=1)3 → kafka(topic="plant.telemetry")4 → flink(window=10s, watermark=allowed)5 → timeseries.warehouse67// SLO: ingest < 2s p99 · loss < 0.01%
1// fintech :: append-only ledger2post(transfer) →3 validate.idempotency_key4 reserve(funds) // double-entry5 emit("transfer.posted")6 → reconciliation.queue78// SLO: post < 120ms p99 · 0 dupes