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INVICTT AI

AI · Automation · Software

Turn repetitive work into intelligent systems.

We design and build AI-powered software, automation workflows and intelligent systems that help organizations work faster, decide with better information, and scale without adding complexity they have to manage themselves.

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Two colleagues mapping out a workflow together at a whiteboard

Document to decision

Your choiceOn-prem, cloud or hybrid
Most of what we build can run entirely inside your network, in a cloud, or a deliberate mix — decided on your constraints, not ours.
Week 3Working system on your data
You see results measured on your own material before committing to a full build — not a demo on someone else's.
YoursCode and systems
Everything we build is handed over with documentation. No licence to us, no migration project if you leave.

01/How it actually works

From manual work to intelligent workflows.

This is the same shape behind every solution in the catalogue — what enters, what the system does with it, and what reaches you.

02/The shift

From scattered manual work to one system.

The same shift, whatever the input — documents, calls, or an internal process nobody owns.
A woman reviewing a printed report against her laptop, a wall of sticky notes behind her

Before

Inputs scattered across inboxes, spreadsheets and phone calls, held together by whoever remembers where everything is.

A man smiling and gesturing at his laptop during a call

After

Automated
Validated
Integrated
Visible

One system, one path, one place to check. The human focuses on the decision; the system handles the repetition.

03/Solutions

All solutions

What can we take off your team's plate?

Six of the strongest examples — the full catalogue is one click away.
A woman looking stressed while working at her laptop, surrounded by desk clutterDocument extraction

Invoice & Document Extraction

Photos and PDFs of invoices, POs and delivery notes become clean rows in your accounting system. Nobody retypes anything.

Ingest → Extract → Review and post

DetailsDiscuss this
A textile worker inspecting fabric by hand on a factory production lineDetection & tracking

Object Detection & Tracking

Counting, monitoring and safety checks from camera feeds, running on the edge rather than streaming everything to a cloud.

Assess → Train → Alert and log

DetailsDiscuss this
A man juggling a phone handset and a radio at once, sticky notes covering his shirtVoice agents

Voice Agents

Phone assistants that book, qualify and answer correctly — for reception, support or lead qualification — and hand over cleanly the moment they should not be handling it.

Connect → Ground → Escalate

DetailsDiscuss this
A technician in a hi-vis vest working on server rack equipmentMCP integrations

Private MCP Integrations

A safe, audited bridge between your internal systems and your AI tools — so agents can act on real data without a blank cheque.

Inventory → Scope → Operate

DetailsDiscuss this

The full catalogue

25 services across 5 categories — custom software, knowledge systems, voice agents, cloud infrastructure and more.

Browse all solutions

Product/Featured product

COHESORA — Accounting practice management, connected.

An intelligent workspace designed to bring accounting-firm operations, client management, documents and workflows together.

An INVICTT AI product

  • One directory for clients, services, deadlines and owners.
  • Invoices read, checked and queued for an accountant to approve.
  • Roles, multi-factor sign-in and per-firm data isolation.

Early access. Free 14-day trial; paid plans are not available yet. The preview uses fictional data only.

Interactive demo Explore COHESORAStart free trial
invictt.com/cohesora
Clients
8
Open tasks
10
To review
3
Overdue
2
Upcoming deadlines
VAT return — Q35d
Payroll run3d
Chase bank statementsoverdue

04/See it, don't just read about it

What exactly can we build for you?

Pick a capability — this is a demonstration of the mechanism, not a live system reading real data.

This is the mechanism behind Document Intelligence.

Discuss your workflow

AI Lab

See AI actually work.

Six systems you can run — the software, the agents, and the data moving between them.

Explore the AI Lab

05/Why a human stays in the loop

AI shouldn't replace the people who understand the work.

It should remove the repetitive parts of it, so they can spend their time on the parts that actually need judgment.
A professional reviewing work at her desk, thinking through a decision
Manual work
AI assistance
Human judgment
Automated actionRepeats

Every solution in the catalogue includes a review step where the stakes call for one — not because the model can't run unattended, but because automation without a judgment checkpoint isn't control, it's just faster guessing.

06/How we work

The full process

Seven stages, from business problem to a system that scales.

Every engagement follows the same shape.

01

Understand

We sit with the people doing the work and measure what it actually costs — before anyone mentions a solution.

02

Design

A concrete solution design — what gets built, what stays as it is, and why — grounded in what week one measured.

03

Build

The system is built against your real data and real conditions from day one — never a demo dataset.

04

Integrate

Connected to the systems you already run — CRM, ERP, databases, internal APIs — rather than becoming another disconnected island.

05

Automate

The repetitive, rule-shaped parts of the work run themselves, with retries, guardrails and alerting on silent failure.

06

Deploy

A supervised ramp, not a switch. Volume moves across gradually while results are watched.

07

Scale

Monitoring, drift review and capacity growth — on a retainer if you want one, or handed over completely if you don't.

07/Work

All work

Real problems. Real systems.

Honestly labeled — no named clients, no invented numbers.
Reference ImplementationAI & Intelligent Automation
TriggerProcessAct

Removing manual invoice entry for a building materials distributor

Two full-time roles spent their mornings retyping supplier invoices into an ageing ERP. We replaced the typing with an extraction pipeline and a review queue — keeping the humans, moving them to the exceptions.

Text-native invoices parse directly from the embedded text layer; only scans and photographs go through the vision pipeline

Building materials distributorRead
Reference ImplementationData, Knowledge & Documents
IngestIndexAnswer

Drafting inspection reports before the inspector gets back to the van

Inspectors were spending their evenings writing up the day's sites from memory and a camera roll. We built an offline-first capture app and a vision model trained on their own defect taxonomy that drafts the report during the visit.

Reports draft the same day as the visit, from photographs taken during the walk rather than reconstructed from memory that evening

Facilities inspection contractorRead
Reference ImplementationData, Knowledge & Documents
IngestIndexAnswer

A policy assistant that never sends a document off-site

Brokers were losing significant time hunting through wordings, endorsements and internal guidance. Compliance had ruled out every hosted AI product. We deployed a fully on-prem retrieval-augmented assistant inside their network.

Runs entirely inside the firm's own network — inference, embeddings and the vector store never leave their infrastructure

Specialty insurance brokerRead

08/Credibility

Our principles

What we actually build with, and how we operate.

Remote-first · collaborating across time zones with organizations worldwide

The stack, honestly

Chosen per engagement, not sold as a package — this is what this kind of work typically uses.

  • TypeScript
  • Python
  • React
  • Next.js
  • FastAPI
  • Postgres
  • PyTorch
  • Hugging Face
  • LoRA / QLoRA
  • YOLO
  • Whisper
  • ONNX
  • TensorRT
  • vLLM
  • Ollama
  • llama.cpp
  • Qdrant
  • pgvector
  • NVIDIA Jetson
  • On-prem GPU
  • MCP
  • LangGraph
  • Structured outputs
  • Eval harnesses
  • OpenTelemetry
  • n8n
  • Redis
  • Celery
  • OAuth / OIDC
  • Webhooks
  • Docker
  • Kubernetes
  • GitHub Actions
  • MLflow
  • Prometheus
  • Grafana

You choose where it runs

On-prem, cloud, or a deliberate mix, decided per component. We build all three, so the recommendation isn't just whatever matches our own stack.

Boring problems pay better

Invoice entry, inbox triage, internal tooling — high volume, low glamour, measurable within a quarter. We'd rather build that than a demo.

Measured, not asserted

A result is a number on your data, or it's marketing. Every engagement ends with a measurement against the baseline — even when the honest answer is that we didn't beat it.

09/Industries

All industries

AI systems built around the way your industry works.

Industry-agnostic engineering, applied to a specific problem — the same solutions, applied to different sectors.

Front-desk call volume and clinical documentation that compete with time spent on patients.

Two clinicians reviewing a scan together on a tabletHealthcare today
A clinician in scrubs smiling at her computer station in a hospitalHealthcare, AI-assisted

Solutions this typically draws on

What is your team still doing by hand?

Show us the workflow. We'll tell you honestly what could become a system — and what it would take.

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