Months of work, delivered in days.
The delay in enterprise delivery was never the engineering. It was the coordination around it, the scoping, the handoffs, the waiting on someone else's sprint. Remove the coordination and the calendar collapses.
Modelled, not measured. These are representative engagements, written to show how scoping and delivery behave. The conventional column is what a delivery organisation would realistically staff and spend. Neither column describes a named customer, and no figure here is presented as a delivered result. Real case studies will appear when design partners agree to be named.
{"projectId": "f8a4cf48-655c-4a82-ad9f-3380324d4c68""status": "BUILDING""tasksCreated": 8"gate": {"contractSigned": true"paymentCleared": true"canKickoff": true}}
What is real: the platform refused to start delivery until the contract was signed and payment cleared, both by verified webhook.
Eight engagements, same two columns.
What a delivery organisation would staff and spend, against what the platform is built to do, and where human error entered in the first place.
Vision inspection on four production lines
Known defect classes, inspected manually, inconsistently between shifts.
Inspection quality drifts by shift, by fatigue, and by who is on the line that day.
- Acceptance thresholds written into the contract before work starts
- The same model applied identically on every shift
- Every classification retained with its evidence frame
Four lines, each needing its own camera placement and calibration on site. Software was ready before the second line was physically ready for it.
Restricted-zone and PPE monitoring, air-gapped
40 existing cameras across four plants. Footage may not leave the site network.
Manual review samples a fraction of footage; breaches are found after the fact, if at all.
- Every frame assessed, not a sample
- Air-gapped constraint captured at intake, before it could invalidate the design
- Evidence clip retained against every finding for audit
Nine buildings, air-gapped, no remote access. Every site is commissioned by someone physically walking it, and that part does not parallelise.
Failure prediction across a historian estate
Years of sensor history that nobody has turned into a warning anyone acts on.
Maintenance runs on a calendar. Condition data is read after a stoppage, not before.
- Failure signatures modelled per asset class, not one global model
- Predictions scored against what actually failed
- Work orders raised with the evidence attached
Historian and PLC data was already centralised, so nothing waited on plant access.
Policy assistant under supervisory review
Staff need answers a supervisor can defend. A confidently wrong answer is reportable.
Staff guess, or escalate. A generic assistant invents a clause that does not exist.
- Refusal is the default when no supporting clause exists
- Every answer carries the clause it came from
- Full query audit log, exportable for supervisory review
Supervisory review runs on the regulator’s calendar, not ours. Build finished in days; the sign-off cycle is most of the elapsed time.
Retrieval across a decade of engineering documentation
Answers exist across wikis, tickets and design docs. Finding them depends on knowing who to ask.
Answers depend on who was asked and whether they remembered correctly.
- Retrieval respects existing document permissions, not just display
- Citation required on every answer
- The same question returns the same sourced answer every time
Cloud, no regulated data, no physical dependency. This is close to the ceiling of what compression can do.
Document intake and exception routing
Documents arrive in every format imaginable and are keyed in by hand.
Manual keying. Error rates rise at exactly the moment volume does.
- Extraction validated against a schema before it is accepted
- Only genuine exceptions routed to a person
- Straight-through rate reported honestly, including what failed
Document formats were known and the finance system had a usable API, so integration was not the bottleneck.
API surface over a system of record that will not integrate
Every initiative routes around the legacy system and pays the same integration tax.
Data re-keyed between systems by people, with no reconciliation.
- Continuous reconciliation so both sides can be trusted
- Incremental cutover with a rollback at every step
- No downtime written into the acceptance criteria
Change windows on the system of record are weekly, so cutover waited on someone else’s schedule twice.
Grounded support deflection
Agents re-answer the same questions; generic assistants get switched off after one bad answer.
A confident wrong answer reaches a customer once and the whole programme loses trust.
- Answers only where a supporting source exists
- Low confidence escalates to a human with context attached
- Deflection and quality metrics exposed, not hidden
Existing ticket history, SaaS integrations and no compliance gate.
Correctness is structural, not diligence.
Human delivery error is not carelessness. It is what happens when a requirement is captured in one person's notes, interpreted by a second, built by a third and tested by a fourth who never read the original.
One record, no re-interpretation
The requirement extracted at intake is the one priced, written into the contract, built against and tested against. Nobody re-types it into a ticket.
Acceptance written before work starts
The criteria are in the signed document. Delivery is measured against what was agreed, not against what someone remembers agreeing.
No handoff, no queue
Work does not wait for the next person to have capacity. The step that follows starts when the one before it finishes.
Refusal over invention
Where the system cannot support an answer, it says so. A wrong answer delivered confidently costs more than no answer.
We would rather have three real references than thirty invented ones.
We are taking a small number of design-partner engagements. You get direct access to the engineers building the platform and influence over the roadmap; we get a case study we can put our name to, with measured numbers replacing the modelled ones on this page.
Apply as a design partner- A real problem with a budget owner behind it
- Access to the data and systems the solution needs
- Permission to describe the outcome once delivered
- Design-partner pricing for the initial engagement
- Direct line to the delivery team, not an account manager
- Influence over the roadmap while it is still cheap to change