Local AI Integration

Local AI Integration for privacy-conscious businesses

Deploy AI workflows, assistants and knowledge systems that run on your own infrastructure, private cloud, or controlled environment, reducing reliance on public AI tools while keeping your data governance tighter.

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Private AI workflows

Internal knowledge assistants

Local or controlled deployment options

Built for sensitive business data

The problem

Public AI tools are powerful, but they are not always appropriate

The productivity case for AI is clear, and teams are not waiting for permission. People are already pasting client details, draft contracts and internal notes into public AI tools because it helps them get work done faster.

For many businesses that is a growing risk rather than a quiet win. Client data, legal documents, financial records, internal strategy and intellectual property all need tighter controls than a public tool can offer. The challenge is to keep the productivity without creating unmanaged data risk:

Sensitive data pasted into public tools

Client and matter confidentiality

Compliance and regulatory obligations

Intellectual property and strategy leakage

Limited visibility over how AI is used

Pressure to adopt AI responsibly

Local AI gives leadership more control over usage, access and governance, so teams get the benefit of AI within boundaries the business has actually set. It works alongside a connected AI integration rather than replacing the tools that already serve you well.

The solution

Build AI systems around your data, infrastructure and risk profile

We design AI systems that fit your data, your infrastructure and your appetite for risk, not the other way around. Each capability below can run in an environment you control.

Local LLM deployment

Open-weight language models running on infrastructure you control, so prompts and outputs stay inside your environment rather than a public tool.

Private knowledge assistants

Internal assistants grounded in your terminology, processes and documents, available only to staff you authorise.

Internal document search and RAG

Retrieval-augmented generation that answers questions from your own knowledge base, with citations back to the source document.

AI workflow automation

Document-heavy and repetitive tasks automated within your perimeter, with human review built in where judgement matters.

Secure prompt and access controls

Role-based access, prompt governance and logging so leadership keeps visibility over how AI is used across the business.

Model selection and optimisation

We match the model and architecture to your accuracy, cost and data-control needs rather than defaulting to one vendor.

Use cases

Where local AI creates immediate value

Most engagements start with one or two high-value use cases and expand as confidence grows. These are the applications that tend to pay for themselves first.

Legal document review and matter research

Surface clauses, precedents and relevant matter history in seconds, with every answer traceable to its source.

Internal policy and compliance assistants

Give teams an assistant that answers from your current policies, procedures and regulatory guidance.

Client service knowledge bases

Make institutional knowledge instantly searchable so client questions are answered consistently and quickly.

Proposal, tender and report generation

Draft proposals, tenders and reports grounded in your own templates, case studies and approved language.

Sales and marketing intelligence

Pull insight from your CRM, content and market data to support sharper outreach and positioning.

Operations and admin automation

Automate the document handling, summarising and routing work that slows operational teams down.

Private coding and technical assistants

Support developers with an assistant that understands your codebase without exposing it to public tools.

Who it is for

Built for businesses that handle sensitive data

We work with teams where a single data leak carries real commercial, legal or reputational cost. The applications differ by sector, but the need for control is constant.

Law firms

Matter research and document review
Internal precedent search
Client confidentiality controls

Accountants

Document and ledger intelligence
Policy and compliance assistants
Report and filing support

Financial services

Research and analysis assistants
Compliance knowledge systems
Auditable AI usage

Healthcare and private clinics

Internal knowledge bases
Admin and intake automation
Tighter handling of sensitive records

Agencies with sensitive client data

Client knowledge separation
Proposal and content support
Controlled access by account

Privacy-conscious SMEs

AI productivity with governance
IP and strategy protection
Clear usage and access policies

Deployment options

Choose the right level of control

There is no single right answer. The right architecture depends on your data sensitivity, your team and your budget. We recommend the right option after discovery rather than forcing every client onto local hardware.

Option A

Controlled cloud AI

For teams that want better governance over AI without managing infrastructure. We configure access, usage controls and data handling around managed services.

Best when speed and low overhead matter and your data sensitivity is moderate.

Option B

Private cloud AI

For businesses that need stronger data boundaries and custom workflows. Models and pipelines run in a private cloud environment you control.

Best when you want custom AI workflows with tighter boundaries than public tools allow.

Option C

Local and on-device AI

For highly sensitive workflows where data control, latency or offline operation matters. AI runs on your own hardware, including air-gapped setups where required.

Best when data must stay on premises or when offline operation is a hard requirement.

Compliance and governance

Designed with governance from day one

Governance is not a layer we add at the end. We build it in from the start so the system is something your leadership, clients and regulators can stand behind.

AI usage policies

Clear, practical policies for how teams may and may not use AI, written to fit how your business actually works.

Access permissions

Role-based access so the right people reach the right systems and data, and no one reaches what they should not.

Audit trails where appropriate

Logging of access and activity to support oversight and give you a defensible record of AI usage.

Data minimisation

Systems designed to use only the data they need, reducing exposure and keeping handling proportionate.

Human review points

Humans kept in the loop at the steps where judgement, accountability or risk make review essential.

Model risk assessment

A structured view of where a model could be wrong, biased or misused, with controls matched to the risk.

ISO 42001-aligned thinking

AI governance shaped by the thinking behind the ISO 42001 AI management standard.

ISO 27001-aligned awareness

Security decisions informed by the principles behind the ISO 27001 information security standard.

References to ISO 42001 and ISO 27001 describe the standards that inform our approach. They do not imply that Generativ holds either certification.

How we work

From AI opportunity to working system

A structured path from first conversation to a governed, working system, grounded in our wider AI strategy and operating design methodology.

Discovery and risk mapping

We map your data sensitivity, compliance obligations and the outcomes that would justify the investment.

Workflow and data audit

We document where knowledge lives, who needs it and how work actually flows across the team today.

Model and infrastructure recommendation

We recommend the architecture, controlled cloud, private cloud or local, that fits your constraints rather than forcing one model.

Prototype build

We build a working prototype against a real use case so you can judge value before committing to a full rollout.

Testing, guardrails and governance

We validate against real workflows and put the access controls, guardrails and governance framework in place.

Deployment and team enablement

We deploy inside your environment and train your people to use, trust and oversee the system day to day.

Why Generativ

Performance marketing thinking meets practical AI implementation

We come at AI from a commercial background in automation, tracking, data flows and growth systems. That means we are interested in what AI does for the business, not AI for its own sake.

We translate business problems into working AI workflows and stay focused on measurable operational value. More about the team behind this work is on our about page, alongside our full solutions library.

Commercially focused, not selling AI for novelty
Experienced in automation, tracking and data flows
Able to translate business problems into working AI workflows
Focused on measurable operational value
Honest about where local AI does and does not fit

FAQ

Local AI integration: frequently asked questions

What is local AI?

Local AI describes AI systems that run on infrastructure you control, whether that is your own hardware, a private cloud or a tightly governed cloud environment, rather than a public AI tool. The aim is to keep more control over where your data goes and how AI is used across the business.

Is local AI better than ChatGPT or Claude?

It is not about better or worse, it is about fit. Public tools like ChatGPT and Claude are excellent for many tasks. Local AI is the right choice when you need tighter control over sensitive data, governance and access. We often recommend a mix, keeping sensitive workloads local and using managed tools where they are appropriate.

Do we need to buy expensive hardware?

Not necessarily. Deployment can run in a controlled cloud, a private cloud or on your own hardware. We assess your requirements first and recommend the option that balances data control, performance and cost, rather than pushing every client towards local hardware.

Can local AI work with our existing documents?

Yes. Using retrieval-augmented generation, an assistant can answer questions grounded in your own documents, with citations back to the source. Most common formats can be connected, including PDFs, Word documents, spreadsheets, contracts and records held in internal systems.

Is this suitable for law firms or regulated businesses?

It is often a strong fit for law firms, accountants, financial services and other regulated or privacy-conscious businesses, precisely because it gives you more control over data, access and governance. We design each system around your specific obligations rather than a generic template.

Can you help us create an AI usage policy?

Yes. A practical AI usage policy is part of how we approach governance. We help you set out how teams may use AI, who has access to what, and where human review is required, written to fit how your business actually works.

How long does implementation take?

A focused prototype against a real use case can be running in a matter of weeks. A fuller production deployment with governance and team enablement typically spans a few months. We scope timelines precisely during the Local AI Consultation.

Can this integrate with our CRM, website, or internal systems?

Yes. Local AI can connect into your broader workflows, including your CRM, website and internal systems, so private intelligence supports the tools your team already uses. We scope the integrations alongside the wider build.