AI, data & automation engineering
Aviox brings the workflow, data, model and software around an operational problem into one delivery path. Services are scoped around the system you need to run, not a list of technologies you need to buy.
Service catalogue
Every engagement starts with the process, not the platform. We size the opportunity, prove it on a narrow slice, then scale it with the engineering discipline that keeps it running on a Tuesday afternoon six months later.
Grounded generation and retrieval over approved enterprise sources: RAG pipelines, prompt architecture, evaluation harnesses and the guardrails that keep answers within policy.
Explore serviceTool-using agents for bounded tasks across your systems, with explicit permissions, state, retries and escalation, and every step logged for audit.
Explore serviceClaims, invoices, KYC packs and contracts read with OCR and structured extraction, validated against business rules, with uncertain fields routed to a person before anything is written back.
Explore serviceForecasting, scoring and anomaly-detection models built on data you can defend, with evaluation, drift monitoring and explainability designed in from the first experiment.
Explore serviceThe operational layer around models: CI/CD, versioned datasets, evaluation gates, retraining, controlled rollouts and cost-aware inference.
Explore serviceIngestion, transformation, quality and evaluation layers on which reliable analytics and AI depend: governed, cloud-native pipelines with tests and lineage.
Explore serviceConnect forms, email, documents, APIs and systems of record into workflows with explicit states and exception owners, using rules where a rule is enough and AI where the task needs it.
Explore serviceWeb applications, internal tools and integration layers built around the process. Where legacy systems must remain, they are isolated behind stable interfaces rather than replaced in a risky first step.
Explore serviceLeast-privilege access, redaction, model and prompt versioning, role-scoped retrieval, logging and continuous evaluation, engineered to a design your risk and legal teams approve.
Explore serviceAlso Cloud & DevOps engineering Product design & UX for AI AI managed services & 24/7 support Assistant & chatbot development MVP engineering
Where these services ship
Most people arrive knowing the process that hurts, not which of the nine services fixes it. Start from your industry instead — each page shows the same five-step pattern in your own vocabulary, with the products and the stack behind it.
By industry
Claims and underwriting operations: intake, extraction, triage and servicing with evidence-backed work queues.
Explore the sector Industry 02Lending, KYC and servicing: document-heavy, rules-aware processes with auditable review and human approval.
Explore the sector Industry 03Intake, referral and clinical administration with source evidence, role-based access and human review.
Explore the sectorAlso Logistics Retail & Commerce Public Sector Legal Education Real Estate Media & Publishing
Or see it already built
Software Aviox builds and operates itself, where product decisions, AI behavior and reliability are our own responsibility.
See the products LifecycleThe lifecycle every one of these services runs inside — evaluation before the feature, release behind a flag, and a loop that never closes.
See the lifecycle Case studiesEvery study states its problem, baseline, architecture, controls and measured outcome, and is published only with the required client permissions.
Read the case studyRequest a quote
Scope the smallest useful production path with an engineer.
How to engage
Most clients begin with an assessment, prove one workflow, then expand. You can enter at the step that matches how much is already known.
We map the process, the data and a measurable baseline, then propose a first production slice with the controls it needs.
One workflow taken to real users on real data, with evaluation, guardrails, monitoring and a rollback plan.
Where the main constraint is the existing application or data layer, legacy systems are isolated behind stable interfaces before anything is replaced.
Technology ecosystem
We pick proven technology for each problem and connect it cleanly to the systems you already run — no rip-and-replace, no lock-in by default.
Every technology on this page is clickable. Each one opens the stack page it belongs to, where you can see what we actually use it for and which products and industries it is already running in.
The model, retrieval and evaluation layer — and the evaluation harnesses that gate every release before it ships.
Governed pipelines, tested transforms and lineage back to source — the layer that decides whether any model above it can be trusted.
The layer your users actually touch: deliberately conservative choices, multi-tenancy from day one and accessibility handled as engineering.
Reproducible environments, observability that notices quality drifting, and the inference cost controls that keep the unit economics honest.
Questions
The things engineering and procurement teams ask us most often when an AI programme is on the table.
AI and intelligent automation (generative AI, retrieval, agents and document intelligence), data engineering and machine learning, process automation and integrations, product engineering and modernization, and the cloud and governance work needed to run them in production.
Yes, where the code, data, evaluation results and deployment setup can be reviewed. We start by checking what the pilot does, how it was tested and what stands between it and production, then decide whether to harden it or rebuild parts of it.
Usually. The architecture keeps model access, retrieval and business logic separable, so a client-selected provider can be used where it meets security, residency, quality and cost requirements. Specific providers are confirmed during scoping.
Pricing is scoped to the workflow and delivery model; packaged pricing is currently unspecified.
Yes. A workflow assessment can stand alone and produce a baseline, a proposed boundary and a first production slice that you can take forward with Aviox or with another team.
Insurance, banking and lending, healthcare, logistics, retail, legal, education, real estate and the public sector. The engineering pattern repeats, but the business rules, data, decision rights and evidence requirements are specific to each sector and each client.
With whichever of the three starting points fits: a workflow assessment when the problem is unclear, a production pilot when the workflow and baseline are known, or a modernization engagement when the existing application or data layer is the constraint.
Ownership of deliverables and of pre-existing materials is set out in the statement of work and in our Terms & Conditions.
Acceptance tests are agreed early, cases are evaluated against the original baseline, and cost controls and monitoring are part of what we build rather than an afterthought.
Request a quote
Tell us the workflow, the data and the system it has to connect to. We will come back with a first slice, the controls it needs and how we would measure it.
