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PRACTICE 01

Custom LLM &
On-Premise AI Deployment

Your organisation's intelligence layer. Trained on your knowledge. Running on your infrastructure. Data never leaves your controlled environment.

Setup: 4–8 weeks|ROI: 60–90 days|Ongoing updates included
OVERVIEW

What This Is


Most organisations have spent years accumulating knowledge — procedures, client histories, compliance frameworks, product specifications, training materials, meeting notes, contracts. That knowledge exists in documents, folders, and email threads that almost nobody reads.

A Custom LLM transforms that accumulated knowledge into an always-available, instantly-queryable intelligence layer accessible to every member of your team, every hour of the day.

It is not a chatbot. It is not a generic AI tool with your company name on the login screen. It is a language model trained specifically on your organisation's knowledge base — deployed on your infrastructure, governed by your policies, and producing answers that reflect your actual expertise.

THE FRICTION

The Problem It Solves


A Custom LLM eliminates all four problems simultaneously.

01

Knowledge is locked

Critical information lives in the heads of three people, a folder no one opens, or a document last updated in 2021. When those people are unavailable, the business slows.

02

Onboarding takes too long

New employees spend weeks asking questions, reading manuals, sitting in handover meetings — before they can operate independently. Every week of reduced productivity has a cost.

03

Meetings transfer information

A significant proportion of recurring internal meetings exist solely because people cannot find answers on their own. This is a systems failure, not a culture one.

04

Client teams are inconsistent

When product knowledge, pricing rules, and compliance requirements live in different places, different team members give different answers. This creates risk.

THE CAPABILITIES

What's Included


Knowledge Architecture & Ingestion

  • Complete audit of your organisation's existing knowledge assets
  • Structured ingestion of SOPs, policies, product docs, contracts, & history
  • Data cleaning, deduplication, and categorisation before model training
  • Custom taxonomy built to match how your organisation communicates
  • Ongoing ingestion pipeline so new documents are absorbed automatically

Model Training & Deployment

  • Custom LLM designed, trained, and fine-tuned on your specific knowledge base
  • On-premise or private cloud deployment — data never leaves your infrastructure
  • Choice of deployment: fully air-gapped on-premise, private cloud, or hybrid
  • Model size selected based on infrastructure constraints & query complexity
  • Natural language interface with source citations included in every response

Integration & Access

  • Web-based query interface accessible from any internal device or browser
  • API access for integration with CRM, ERP, Slack, Teams, or intranet platforms
  • Role-based access control — different teams see different subsets of data
  • Audit log of all queries to identify common questions and knowledge gaps
  • Optional client-facing deployment — public AI assistant trained on product specs

Intelligence & Reporting

  • Live ROI Dashboard tracking hours recovered, meetings replaced, and savings
  • Weekly usage reports displaying most queried topics and unanswered questions
  • Quarterly knowledge health reviews to locate outdated or conflicting data
  • Escalation flagging for queries falling outside current model training scope

Ongoing Partnership

  • Model updates and iterative fine-tuning as your organisation evolves
  • Continuous data expansion to absorb new documents, specifications, and SOPs
  • Ongoing model performance monitoring and response accuracy benchmarking
  • Dedicated account contact for all technical, architectural, and strategic support
PROCESS

How It Works


01
Week 1–2

Discovery

Audit knowledge assets, define taxonomy, design ingestion architecture, and agree on deployment model.

02
Week 3–4

Ingestion

Knowledge assets are ingested, cleaned, and prepared. Fill critical gaps with your team before training.

03
Week 5–6

Training

Model is trained on your prepared knowledge base. Internal testing and accuracy benchmarking.

04
Week 7–8

Deployment

Deploy to infrastructure, configure access control, integrate tools, and run team training.

05
Ongoing

Improvement

Monthly check-ins, quarterly knowledge reviews, and model updates based on query logs.

SECURITY FIRST

Why On-Premise Matters


The alternative to on-premise deployment is sending your organisation's knowledge — your procedures, your client data, your competitive intelligence — to a third-party cloud. For many organisations, particularly those in financial services, legal, healthcare, manufacturing, or defence-adjacent sectors, this is not a viable option.

Data never leaves your infrastructure

Not to train a model elsewhere. Not to improve a vendor's product. Not to be stored in a shared or public cloud environment.

Zero external vendor dependencies

You are not dependent on a third-party vendor's uptime, sudden pricing changes, or product lifecycle decisions. The model runs on hardware you control.

Flawless compliance governance

Meet your compliance and data governance requirements (such as GDPR, ISO, or HIPAA) without exceptions, special API terms, or workarounds.

Permanent competitive advantage

A knowledge base trained on years of your organisation's unique expertise is not something a competitor can replicate by switching on a SaaS subscription.

OUTCOMES

Results You Can Expect


These are directional benchmarks from comparable deployments. Outcomes vary by organisation size, knowledge base complexity, and usecase constraints.

60–80%Onboarding time reduction
25–40% reductionInternal meetings eliminated
Under 30sQuery response time
80%+ active useKnowledge base utilisation
60–90 daysROI timeline
TARGET AUDIENCE

Who This Is For


10–200 Employees

Founder-Led & Family Businesses


Where critical knowledge is concentrated in a small number of people and the founder is frequently the single point of failure.

Law, CA, & Consulting

Professional Services Firms


Where deep expertise, regulatory knowledge, and case history are the core product and need to be accessible instantly.

Operations & Specifications

Manufacturing & Industrials


Where product specifications, compliance documentation, and operational procedures are extensive and critical.

Accelerated Onboarding

Rapidly Scaling Teams


Growing businesses undergoing rapid hiring where onboarding speed directly affects client experience.

Preserving Institutional Knowledge

Succession & Transition


Organisations preparing for succession where institutional knowledge needs to be documented and systematised.

FAQ

Frequently Asked Questions


What data formats can you ingest?
PDF, Word, Excel, PowerPoint, plain text, HTML, email archives, Notion exports, Confluence exports, Google Drive, SharePoint, and custom database exports. If your knowledge lives somewhere we have not listed, we will find a way to ingest it.
What if our documentation is incomplete or outdated?
This is the norm, not the exception. Part of the discovery phase involves identifying gaps. We work with your team to fill critical gaps before training begins and flag lower-priority gaps for your attention.
Can different employees see different information?
Yes. Role-based access control is built into every deployment. Your sales team sees sales knowledge. Your compliance team sees compliance documentation. Nobody sees what they should not.
How is accuracy maintained over time?
The model is re-trained on an agreed schedule as your knowledge base grows and changes. We also monitor query logs for unanswered questions — these become the inputs for the next training cycle.
What happens if the AI gives a wrong answer?
Every response includes source citations. Employees are trained to verify answers against sources when the stakes are high. We build escalation pathways for questions the system cannot answer with sufficient confidence. Over time, these pathways feed back into improving the model.
Is this the same as using ChatGPT with uploaded documents?
No. Consumer AI tools with document upload are general-purpose models that treat your documents as context for a single session. A Custom LLM is trained on your knowledge base — it understands your terminology, your product names, your internal conventions, your compliance requirements — and retains that understanding permanently, not just for one conversation.
ENGAGEMENT MODEL

Ready to deploy your organisation's intelligence layer?

Custom LLM deployments are scoped individually. Every organisation has a different knowledge base, different infrastructure constraints, and different use cases.

The process begins with a consultation. We assess your knowledge assets, your infrastructure, your team size, and the specific outcomes you need. A detailed proposal — covering scope, timeline, investment, and expected ROI — is delivered within 48 hours of that conversation.

There is no obligation after the consultation. We will tell you honestly whether this is the right solution for your organisation, and if it is not, we will tell you what is.

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