01 / KNOWLEDGE
Retrieval systems
Answers grounded in your documents, with citations, permissions, and a review path when confidence is low.
Software + AI engineering studio
We build the engine, not just the interface.
Newtonly designs and deploys custom AI systems and production software. We solve the hard engineering behind the chat box—and make sure your team can own what ships.
SYSTEM / LIVEREADY
YOUR DATA
Documents + tools
NEWTONLY
Decision layer
Evaluate
Review
Deliver
Human review stays in the loop where it matters.
02 / OPERATIONS
Document workflows
Classification and extraction for real paperwork, connected to the systems your team already uses.
03 / DECISIONS
Forecasting & scoring
Measured models with clear baselines, evaluation sets, and limits your operators can understand.
THE NEWTONLY METHOD
A clear route from messy process to working system.
01
Scope
Map the workflow and agree what good looks like.
02
Prototype
Test a narrow version against your real data.
03
Harden
Add evaluation, guardrails, logging, and fallbacks.
04
Hand over
Your code, your cloud, and documentation your team can use.
WHERE IT EARNS ITS KEEP
Useful AI starts with a real piece of work.
We do not begin with a model or a feature list. We begin with the work your team repeats, the decisions that slow them down, and the information they cannot reach quickly enough.
Explore our servicesTurn scattered knowledge into useful answers
Give teams one place to ask questions across policies, contracts, manuals, and past work—with sources attached and permissions respected.
Less searching. Fewer repeated questions.
Move documents without manual re-keying
Read incoming forms, invoices, claims, and reports; extract the right fields; then route exceptions to the person who should review them.
Faster handling without hiding uncertainty.
Help teams respond with context
Bring account history, product guidance, and approved language into the workflow so service teams can answer clearly and consistently.
Better responses, with people still in control.
Spot the cases that need attention
Score demand, risk, quality, or urgency against agreed criteria and show operators why an item was prioritised.
Clearer queues and more informed decisions.
CONNECTED
Fits the systems you already use
APIs and workflows connect the new capability to your existing tools instead of creating another isolated destination.
MEASURABLE
Tested against real examples
We agree on a baseline, build an evaluation set, and track quality, cost, and response time as the system changes.
TRANSFERABLE
Built for your team to own
Readable code, documented decisions, and clear operating limits mean the system does not depend on us staying forever.
WHO WE WORK WITH
Operations-heavy businesses with more process than headcount.
We work best with teams who already know which part of their day is painful. The sector matters less than the shape of the problem: repeated judgement calls, documents moving between systems, and knowledge locked inside a handful of experienced people.
Professional services
Firms whose value sits in precedent, templates, and past matters — and whose juniors spend hours locating them. We make that history searchable with sources attached.
Knowledge retrieval
Logistics and supply chain
Paperwork moves before the freight does. Bills of lading, customs documents, and delivery notes get read, checked against your rules, and routed when something looks wrong.
Document operations
Financial operations
Reconciliation, onboarding checks, and exception queues where the rules are known but the volume is not. We automate the routine and surface what needs a human.
Exception handling
Healthcare and insurance admin
Intake forms, claims, and eligibility checks where accuracy is not negotiable. Every automated decision keeps an audit trail and an escalation path.
Auditable workflows
Manufacturing and field service
Maintenance logs, technical manuals, and inspection reports turned into answers a technician can get on site, in plain language, from the source document.
Field knowledge
Software companies
Teams adding intelligence to an existing product who need it to behave like a real feature — versioned, tested, monitored — not a bolted-on demo.
Embedded AI
WHAT AN ENGAGEMENT LOOKS LIKE
Short cycles, visible progress, no long silences.
Every engagement runs in two-week cycles with a working demo at the end of each one. You see the system as it is, not as a slide describes it.
Weeks 1–2
Discovery
We sit with the people doing the work, follow the process end to end, and write down where the time and errors actually accumulate.
- Workflow map
- Feasibility note
- Agreed success measure
Weeks 3–6
Prototype
A narrow version running against your real data, so the conversation moves from opinion to evidence early.
- Working prototype
- Evaluation set
- Cost and latency baseline
Weeks 7–12
Production build
Guardrails, logging, permissions, fallbacks, and integrations with the systems your team already lives in.
- Deployed system
- Monitoring and alerts
- Regression test suite
Ongoing
Hand over and run
Documentation, walkthroughs with your engineers, and an optional retainer for upgrades and reviews. You can end it whenever you like.
- Source code and infrastructure
- Runbook and documentation
- Review cadence
HOW WE BUILD
Boring technology, carefully assembled.
We favour tools that are widely understood and easy to hire for. Nothing here is exotic, because the system has to keep running long after we have handed it over.
Languages
TypeScript and Python for application and pipeline code, SQL for anything the database should be doing itself.
AI layer
Frontier and open-weight models behind a provider-agnostic interface, retrieval over vector and keyword search, structured outputs with schema validation.
Data
Postgres, object storage, and incremental pipelines with explicit quality checks and loud failures.
Delivery
Version control, code review, automated tests, containerised deploys, and observability in the cloud account you already own.
WHAT WE DO NOT DO
Being clear about this saves everyone time.
We do not train foundation models
That is a different business with a different cost base. We build on top of models that already exist, and fine-tune only when evaluation shows it earns its place.
We do not sell licences to our own platform
There is no Newtonly product you become dependent on. What we write belongs to you, in your repositories and your cloud account.
We do not staff-augment by the seat
We take responsibility for an outcome, not for filling a chair. If you need bodies on an existing team, another firm will serve you better.
We do not promise numbers we cannot measure
Until there is a baseline and an evaluation set, any percentage improvement is a guess. We would rather show you the first one than quote the second.
QUESTIONS WE GET ASKED
Before the first call.
HAVE A WORKFLOW IN MIND?
Tell us where the work gets stuck.
We’ll tell you honestly whether AI is the right tool—and where we would start.
No pitch deck required.