Infrastructure
Zero vendor lock-in
All code, deployment configuration and models run in your VPC. No licensing fees, no forced dependencies, no black-box APIs.
Approach
AI-native is not a chatbot bolted onto an old process.
It is a better way for work to move from trigger to outcome, with the right context, actions, controls, human decisions and feedback built into the workflow itself, not layered on top of it.
Why this model works
Built so your team can run it, not just watch it run.
We do not sell subscription SaaS or lock you into proprietary platforms. We build production-grade workflow systems directly on your cloud infrastructure and hand over the codebase, the documentation and the operating playbook.
Ownership
True custom IP
The evaluation harnesses, fine-tuning scripts and vector databases are your enterprise assets from day one — not ours, not licensed back to you.
The 45-day AI-native foundation
One priority workflow, redesigned and running in 45 days.
- Days 1–5
- Workflow X-RayWe map the recurring work, decisions, handoffs, systems, delays, rework and risks: the version that is actually happening, not the version in the process document.You geta workflow map, baseline metrics and a prioritised opportunity backlog
- Days 6–10
- Context foundationWe identify the approved data, knowledge, policies, examples and permissions the system needs, and test freshness and access boundaries before any build starts.You geta context and retrieval design, plus a data and access plan
- Days 11–17
- Redesign the workflowWe define the trigger, inputs, decisions, human role, AI role, automation, exceptions, outputs and feedback loop for the priority responsibility.You getan AI-native workflow blueprint with acceptance criteria
- Days 18–24
- Reusable building blocksWe build the retrieval patterns, validations, templates and test cases the workflow will run on, so nothing downstream is improvised.You getreusable workflow components and a test pack
- Days 25–31
- Connect the environmentWe integrate the systems, data sources, tools and interfaces the redesigned workflow needs, with least-privilege access and logging from day one.You getgoverned integrations, not copy-paste bridges
- Days 32–38
- Agentify where justifiedPlanning, tool use, bounded execution, handoffs and retries, only where the workflow actually needs adaptive routing, not by default.You geta working system with defined authority limits
- Days 39–42
- Operate & measureWe run live cases, monitor results, compare against the baseline from day one, and tune what is underperforming.You getan operating dashboard and an evidence ledger
- Days 43–45
- Stress-test & transferWe test missing data, contradictory evidence, low confidence, tool failure, policy conflicts and interruption, then hand the runbook to your team.You getstress-test results, a runbook and a 90-day roadmap
Day 45 is a decision point, not an artificial finish line. You leave with a live, measured foundation for one priority workflow and a clear roadmap to scale it. Larger data migrations, enterprise integrations, compliance reviews or multi-workflow rollouts continue as a separate, scoped build phase.
How it works
AI that earns trust,
not just attention.
We do not drop a model into production and hope. Every system is built around a feedback loop: sense, decide, measure, improve. On the right are the four documents that loop produces — the ones that transfer to you at handover.
01
Sense
Data streams in from documents, APIs, databases and user actions.
02
Decide
The model makes a call with a confidence score and a known failure mode.
03
Measure
Outputs are checked against ground truth; drift triggers retraining.
04
Improve
What failed and what we changed goes in the runbook, in your repository.
Sample handover artifacts
Sense
Source inventory
- orders.csvSFTP · daily 02:00
- billing_apiREST · 15 min
- ledger_dbPostgres · live
Every input named, with an owner beside it. Written in week one.
Decide
Decision record
- ADR-004Match on invoice_no
- RejectedFuzzy match on amount
- OwnerFinance
Why the system does what it does — and what we turned down.
Measure
Check report
- row_count_deltaPASS
- null_ratePASS
- duplicate_keysHELD
Runs on every batch. A failed check stops the batch — it does not warn.
Improve
Runbook
- 01Read the last run log
- 02Re-run from failed step
- 03Escalate: on-call, then us
So your team can fix it at 2am without calling us.
Decision model
Not every step
needs an agent.
Keep
Stays with a person
Judgment, empathy, accountability or ambiguity is the value. A person keeps doing it.
Augment
Improves the person
AI sharpens the research, drafting or preparation. The person still decides.
Delegate
AI produces, a person approves
AI produces a reviewable work product. Nothing ships without sign-off.
Automate
Rules, not a model
The rules and state transitions are stable enough to run without inference at all.
Agentify
Goal fixed, path adaptive
The outcome is clear but the route needs interpretation, tools and observation.
Eliminate
Stops
The work creates no customer, control or learning value. It does not get automated — it stops.
Weekly rhythm
Inside a phase, a build week looks like this.
Total time asked of your side: about ninety minutes a week, plus whatever questions come up in the shared channel.
Build week · cadence
One build week, Monday to Friday.
5 checkpoints
-
Plan
Week plan posted: what ships, what is at risk, and what we need from you.
Plan posted
-
Build
Pull requests reviewed by a second engineer, with read access to everything from day one.
Code reviewed
-
Deploy
Into a real environment. Anything that cannot be deployed is reported as not done.
Build live
-
Demo
Thirty minutes of running software. No slides, and the recording goes out the same day.
Software demoed
-
Burn report
Hours used, hours remaining, and every scope change priced in the week it was raised.
Hours accounted
Governance
Control that lives in the code, not a policy document.
Agentic workflows are only reliable when the control is part of the build. Every system we ship carries these three.
Review
Human in the loop
Critical actions and low-confidence predictions are routed automatically to a reviewer workbench, and wait there until a person releases them.
Review workbench
State
Deterministic states
AI logic is wrapped inside strict state-machine bounds. A model classification can choose the transition; it can never write an arbitrary database record.
State machine
Logging
Full prompt tracing
Every model call is logged with the exact system prompt version, user context, input tokens and output — so a bad answer can be reproduced, not guessed at.
Trace & replay
Measurement
What we track once the system is live.
Four claims stay separate: whether the model is good, whether one task is faster, whether the whole workflow performs, and whether it was worth the money. We do not let a good demo stand in for any of the other three.
- Speed
- End-to-end cycle time for the whole responsibility, not model latency in isolation.
- Quality
- Errors, rework and how often the output is accepted without a human rewriting it.
- Adoption
- Share of eligible work actually running through the new path, not the pilot’s best week.
- Risk
- Exceptions, escalations and audit findings, tracked and visible, not filtered before you see them.
Quality floor
What is included in every build.
Source control, testing, accessibility and security are not upgrades. They ship with the system, or the system is not finished.
- Source control
- Your organisation, your repository, from the first commit. Never ours.
- Testing
- Automated tests on every change, run in CI. Coverage reported honestly, not targeted for its own sake.
- Infrastructure
- Defined as code and reproducible. No environment that exists only because someone clicked through a console.
- Accessibility
- WCAG 2.1 AA on anything with a user interface. Keyboard paths and screen reader labels checked, not assumed.
- Security
- Dependency scanning, secret management and least-privilege access.
- Documentation
- Runbooks for deploy, rollback and failure. Written for the engineer who joins after we leave.
- Exit
- A recorded handover walkthrough and thirty days of questions answered at no charge after the final invoice.
Next
Hold us to it.
Bring the problem. The first call is scoping, not selling, and you should leave it with a clearer view of the work whether or not you hire us.