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The audit fee comes off your buildHow it works

Evoxatech®

Services

Start with the smallest thing that would prove it.

Fixed scope, fixed price, and you know the number before you commit. Most people start at the top of this list and only go further once the first engagement has paid for itself.

Start a project
Shadowing someone's work, notebook in hand
Rows of company archives in a library
Mapping the rules of a process on a whiteboard
Customer conversations handled at a desk
Infrastructure you control, in your own racks
Start here

Automation Audit

Find out what is automatable — before you commit to building anything.

  • Workflow map — 3 to 5 workflows documented end to end, including the exceptions nobody writes down
  • Time and cost model — hours per week × loaded cost = the annual figure you are burning
  • Automation scorecard — every workflow scored on feasibility and annual impact, then ranked
Reviewing a client's workflow together at a laptop
Retrieval

Knowledge Agent

Every answer your company already has, findable in one question.

  • Connectors for Drive, Notion, Confluence, SharePoint, Zendesk, Postgres or your file store
  • Ingestion pipeline with chunking, embedding and incremental re-index as documents change
  • Hybrid retrieval — vector and keyword, because pure vector search fails on names, codes and SKUs
Archive folders of company documents
Flagship

Workflow Agent

We watch how the work is done by hand, then build the system that does it.

  • A signed-off decision document capturing how the work is really done, edge cases included
  • Ingestion from email, web form, API or file drop
  • Structured extraction from unstructured input
Mapping a manual process on a whiteboard
Voice

Voice Agent

Answer every call, book the appointment, and hand the hard ones to a human.

  • Conversation design and scripting for your real call patterns
  • ElevenLabs voice with telephony via Twilio, Vapi or LiveKit
  • Grounded in your actual business information — hours, services, pricing, policies
Customer specialist wearing a telephone headset
Your infrastructure

Private AI Deployment

Open models running on your own hardware. Your data never leaves your perimeter.

  • Model selection and benchmarking on your tasks — Llama, Qwen, Mistral
  • vLLM serving configuration tuned for your traffic shape
  • GPU sizing and cost modelling
Server aisle in a data center
Product

Product MVP Sprint

Idea to deployed product in six to eight weeks.

  • Product and technical scoping, with a scope you sign off before we build
  • Full-stack application — React and Next.js front end, Node or NestJS services
  • Postgres schema, migrations and seed data
Engineers building a product at dual monitors
Ongoing

Operate

Someone owns it after launch — because AI systems decay in ways ordinary software does not.

  • Care — $3,000/mo: monitoring and uptime, bug fixes, monthly report, model and prompt maintenance, 2-day response
  • Operate — $4,500/mo: adds cost optimisation, evaluation re-runs as data drifts, one improvement cycle a month, shared Slack, 1-day response
  • Partner — $6,000+/mo: adds one new workflow a quarter, quarterly roadmap sessions, same-day response and a direct line
Performance dashboard on a tablet