Frontier AI engineering — vertical depth across four industries, horizontal solutions across all of them. Pods of senior engineers and domain experts, embedded with your team, shipping to production.
Enterprises have the data. They have the budget. They have leadership backing. What they don't have is a way to get from “we should be using AI for this” to “this is running in production and moving the KPI.”
The path most firms are sold looks like this: an RFP, six months of discovery, a polished MVP that lives on a laptop, a handoff to a delivery team that never quite owns it, and a year later the executive sponsor has moved on.
We do the opposite. We embed a small pod of senior engineers and domain experts with your team. We pick one use case. We ship it to production in weeks, not quarters. Then we hand off the scale work — but our lead architects stay on so the system doesn't drift.
Every solution is built to be deployed in your workflow, on your data, against your KPIs. Not a demo. A production system.
Policy logic + clinical context + document AI — PA cycles in hours, not days.
Open the briefCoding, denials, patient-financial flows compressed end-to-end against time-to-cash.
Open the briefRegulatory submissions, label change tracking, medical-info drafting — therapeutic-area-tuned agents.
Open the briefDocument AI + adverse-media + relationship-graph synthesis. Cycle time down, case quality up.
Open the briefDocument extraction + policy reasoning + draft credit memo with every covenant explained.
Open the briefCardholder, ACH, and merchant disputes triaged and packaged — time-to-disposition is the metric.
Open the briefSKU × location × week forecasts with weather, events, local effects — overridable by the planning team.
Open the briefMulti-tier visibility, supplier risk scoring, exception routing.
Open the briefInbound classification, disposition routing, reverse-logistics optimisation.
Open the briefOrder, returns, and loyalty triage as agentic workflows — what works here transfers across industries.
Open the briefLabour scheduling, replenishment exceptions, task management across the fleet.
Open the briefDC orchestration, vendor SLA enforcement, inbound exception handling.
Open the brief14–30 day claim cycles compressed to 2–3 days. The same workflow ships into insurance, healthcare payers, and BFSI dispute teams.
Open the briefClose-cycle acceleration, anomaly detection, reconciliation agents — plus the multi-cloud cost-forecasting layer the engineering org runs against the same KPIs as finance.
Open the briefMulti-tier visibility, supplier exception routing, and demand-sensing wired across your existing planning stack. Works for manufacturers, retailers, healthcare distributors, and BFSI ops.
Open the briefThree cross-industry workflows we ship the same way everywhere. What we deploy for a payer's claims team transfers cleanly to a P&C insurer or a card issuer's dispute desk.
The 15 above are where we hit the ground running — pods we've shipped before, with the playbook already written. The pod model is not bounded by them. If you've got a problem that doesn't sit on this list, that's often the most interesting conversation.
“We'd spent two years and a lot of money getting nowhere on this. Their pod was in production in eleven weeks. The difference was that they actually owned the outcome instead of the deliverable.”
“Most consultants leave you with a system you can't maintain. They left us with a system our team understood, documented, and could extend. Their architect is still on a Slack channel with us six months later.”
Tell us what you're trying to ship. We'll come back with a pod composition, a timeline, and a price.