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AI practice for enterprises & SMEs
Cloud · On-premise · Governed by design

Give your business
a voice — and agency.

Your business already owns what AI needs — years of expertise, documents, and judgment. We turn it into AI your workforce and management can talk to: ask the business anything and get cited answers from its own knowledge. Then we give it agency — governed AI that performs real work.

Governed to
NIST AI RMF
ISO/IEC 42001
Law firmsAccounting & advisoryMedical groupsFINANCIAL · SERVICESEngineering practicesInsurancePublic sectorENERGY · UTILITIES Law firmsAccounting & advisoryMedical groupsFINANCIAL · SERVICESEngineering practicesInsurancePublic sectorENERGY · UTILITIES
The pattern

Everyone has AI. Almost no one has it working.

The technology is not the bottleneck. What's missing is the connection between AI and the way your business actually works — its knowledge, its workflows, its people.

95%

of GenAI pilots show no P&L impact

MIT's 2025 State of AI in Business study found only ~5% of enterprise pilots reach rapid value — and the winners empowered line managers, not central AI labs.

~19%

of the working week is lost to searching

McKinsey Global Institute found knowledge workers spend roughly a day a week just looking for information that already exists inside the business.

10-20-70

AI success is mostly people and process

BCG's rule: 10% algorithms, 20% technology and data, 70% people and process. That 70% is where we work — and where most projects never go.

The method

Frontline-first. Five layers.

We don't start with technology selection. We start where work actually happens — then structure, support, govern, and improve from there.

01

Observe

Map how work truly happens — where information slows down, decisions stall, and people rely on workarounds.

02

Structure

Turn scattered documents, drives, and tribal knowledge into a governed, retrievable knowledge layer.

03

Support

Embed AI where decisions are actually made — contextual support at the moment work happens.

04

Govern

Access controls, explainability, human-approval thresholds, and audit trails — aligned to NIST AI RMF and ISO/IEC 42001.

05

Improve

A monthly operating rhythm: feedback, telemetry, new workflows shipped, and your own people trained as champions.

Observe → Structure → Support → Govern → Improve — run as a repeating cycle, not a one-off project.
The full method
Where to start

Start with a readiness assessment.

Fixed fee, evidence-based, and useful on its own — it ends with a scorecard, a prioritized shortlist, and a 90-day roadmap. Two scopes, depending on how deep you want to go.

SCOPE 01 · SURFACE SCAN
1–2 weeks
Where does
work get stuck?
Interviews-led · Fixed fee from US$2,500

A structured read on your AI readiness, built from conversations with the people who run the work — leadership and frontline.

  • Stakeholder & frontline interviews
  • Readiness scorecard across 7 dimensions
  • Friction snapshot with top-3 opportunities
  • Executive debrief + written summary
Book a surface scan
RECOMMENDED
SCOPE 02 · DEEP DIVE
3–5 weeks
What should
we build first?
Interviews + document & data analysis · Quoted to scope

Everything in the surface scan, plus an analysis of your actual documents, SOPs, and data — the evidence that turns a roadmap into a build plan we can quote as a fixed price.

  • Document, SOP & knowledge-base analysis
  • Data-readiness review & knowledge inventory
  • Use-case scoring & governance gap review
  • 90-day roadmap + build blueprint
Book a deep dive

Both scopes are fixed-fee and stand on their own — no obligation to build with us. If you do, the assessment fee is credited against the build.

Deployment

Your knowledge never leaves your control.

Everything we build runs where you decide. Your data, your knowledge base, and every output belong to you — unconditionally. We keep our delivery framework; you keep everything it produces.

That's not a feature. It's the reason risk-aware organizations can say yes.

Cloud

Fast to stand up, fully managed

Deployed in a private cloud tenancy with role-based access, encryption, and audit logging. The default for teams that want speed without giving up control.

On-premise

Inside your own infrastructure

For regulated and data-sovereign organizations: the full system runs on your servers or in your private cloud, within your identity, hosting, and logging constraints.

Case study
Professional services · Law

A 30-year law firm gave its expertise a voice — then a teammate.

Decades of authority — articles, opinions, case knowledge — locked in a legacy website and scattered archives, invisible to the AI engines clients now ask first. We rebuilt it as firm-owned AI infrastructure, in phases.

Read the case study
Tool

An AI-ready foundation

A fast, machine-readable web presence with full structured data — built so both people and AI engines can understand who the firm is and what it knows.

System

A knowledge engine

The firm's archive became a private digital memory and a publishing engine — answer-first content structured to earn citations from AI search, owned by the firm.

Teammate

A private co-pilot

The same memory turned inward: a multi-agent assistant that researches, retrieves, and drafts against the firm's own knowledge — with review gates and evaluation before anything ships.

Common questions

What we hear most often.

Something not covered here? Write to us directly.

How does an engagement start?

With a fixed-fee readiness assessment, in one of two scopes: a surface scan built from stakeholder and frontline interviews, or a deep dive that adds analysis of your documents, SOPs, and data. Both end with a readiness scorecard, a prioritized shortlist, and a 90-day roadmap — useful whether or not you build with us.

Can this run on our own infrastructure?

Yes. Everything we build deploys either in a private cloud tenancy or fully on-premise, inside your identity, hosting, and logging constraints. Your knowledge never leaves your control — that is a design principle, not an add-on.

Who is this for?

Businesses that run on expertise — from established professional-services firms to enterprise operations teams. If your organization has real knowledge trapped in documents, systems, and people's heads, both the voice and agency practices apply. We work with enterprises and SMEs, and scale the engagement to fit.

How do you keep it governed?

Governance is engineered in, not written up afterwards: role-based access controls, human-approval thresholds for consequential actions, evaluation of groundedness and citation accuracy, and audit trails — aligned to NIST AI RMF and ISO/IEC 42001. You get the policy pack and the controls, and they are designed to be operated, not filed.

Does this replace our people?

No — it strengthens their judgment. We start every engagement with the people doing the work, and the operating model trains your own champions so capability builds inside your team, not ours. The evidence is clear that AI value is mostly people and process; systems designed around your people are the ones that get adopted.

Who owns what when an engagement ends?

You own your data, your knowledge base, and every output — unconditionally, in machine-readable form. We retain the reusable delivery framework we bring to every client. That line is written into every agreement.

Start here

Give your business
a voice — and agency.

A fixed-fee readiness assessment that ends with a scorecard, a shortlist, and a 90-day roadmap — whichever scope fits.