For problems that deserve a senior team.
A small number of partnerships per year. The same engineers who built the SDK. Narrow scope, shipped deliverables, no slide decks.
What this is
A narrow partnership track for organisations tackling a complex AI/ML problem or a critical piece of system software, where senior engineering depth is the difference between shipping and slipping.
In practice, that means
- A small number of partnerships each year, owned by the same senior team that builds the product line.
- Problem framing first: the work starts by constraining scope, interfaces, risks, and success criteria.
- Shipped deliverables over presentations: prototypes, binaries, benchmarks, documentation, or decision-ready technical memos.
- Clear boundaries: no open-ended staff augmentation, no diffuse roadmaps, no side work that competes with the product line.
The point is not to sell generic capacity. The point is to apply the same depth that built the SDK where it genuinely changes the outcome.
Capabilities
The work stays close to the kinds of problems we already solve for ourselves: imaging-AI engineering, numerical pipelines, performance work, and documentation that product teams can use.
Applied imaging AI
Focused work on segmentation and adjacent imaging problems where mathematical structure, data provenance, and release discipline all matter.
Typical work
- Problem framing around the exact output a product team needs.
- Evaluation plans tied to release decisions rather than demo moments.
- Pipeline design that stays legible to engineering and quality stakeholders.
Numerical and performance work
Optimisation of runtime, memory posture, and cross-platform behaviour for software that has to live inside a customer-facing product.
Typical work
- Volume-processing pipelines and geometry-sensitive pre-processing.
- GPU and CPU performance work where latency and reproducibility both matter.
- Interface design that keeps external integrations stable as internals evolve.
What we optimise for
- Predictable release behaviour.
- Clear technical boundaries.
- Work that can be maintained after handoff.
Product and quality support
Engineering artifacts paired with the documentation an internal product, quality, or regulatory team can actually put to work.
Typical work
- Release notes, validation summaries, and interface documentation.
- Risk-aware technical memos for build-versus-buy or roadmap decisions.
- Documentation packs that help an internal team move from prototype to product.
Engagement
The engagement path is deliberate: discovery sprint, scoped delivery, optional extension only when the case stays clear.
Discovery sprint
A short, senior-led phase to frame the problem, map constraints, and decide whether a deeper engagement is justified.
- Technical scope and success criteria.
- System constraints, risks, and external dependencies.
- Whether the problem is genuinely worth solving now.
Deliverable: scoped problem statement, technical risks, and a recommendation on whether to proceed.
Scoped engagement
A bounded work package with explicit deliverables, a named owner, and a timeline that matches the problem rather than a generic retainer model.
- Clear interfaces and decision points.
- Benchmarks or artifacts that can be reviewed in context.
- Documentation that leaves the internal team stronger than before.
Deliverable: shipped technical output with the documentation needed to use it.
Optional extension
Further work only if the first scope lands cleanly and both sides still see a precise next step.
- Product fit after the initial delivery.
- New scope that is concrete rather than aspirational.
- A reason to continue that survives sober review.
Deliverable: a defined next phase, not an indefinite attachment.
Who this is not for
This track exists for a specific kind of problem and a specific kind of buyer. It is not the right door for everything.
Clinics looking for a direct operational tool rather than an OEM-facing software component or engineering partner.
Direct-to-patient products or anything that would blur the line between component vendor and finished-device manufacturer.
Projects that conflict with the roadmap of the product line we are already building.
Arrangements that expect transfer of our core product IP rather than delivery against a defined scope.
Need depth on a complex AI/ML problem or critical piece of system software?
If the problem is narrow, material, and worth a senior team, start the conversation.