The sovereign AI stack for regulated enterprise

Most AI vendors send your data to the model.We send the model to your data.

BizfyLabs builds the runtime that puts open-weight models, governance and audit inside your own perimeter, air-gapped, in your data centre, or in your cloud tenancy. You hold the keys. You control the weights. Nothing leaves.

Talk to BizfyLabs See the architecture

Private AI runtime on hardware you control, open weights, gateway and applications in one stack

Same stack. Your perimeter, or no network at all

AWS
Azure
GCP
NVIDIA
Linux
Kubernetes
Air-gapped

Open-weight runtimeLLMs, RAG and agents, Apache 2.0 and MIT only
Controls in the pathPolicy, DLP and audit on every prompt
Runs where you runAir-gapped, private cloud or your tenancy
You hold the keysCustomer custody in every deployment tier

Architecture

One private AI runtime.Built around your environment.

Install once, review once, and never repeat either. Both applications run on the same Foundation, so adding the second one costs you no new deployment, no new procurement cycle and no new security review.

Application

DocxIntel

Reads what your organisation receives. Arabic and English in the same document, including handwriting, with a confidence score and a citation back to the page for every field.

Application

AgentLab

Acts on what those documents said. Reaches the systems you already run, holds consequential actions behind a named approver, and logs every step.

The runtime

Private AI Foundation

Where your sovereignty is actually enforced. Open weights on your hardware, policy and DLP in the path of every prompt, and an immutable audit trail, not a report produced afterwards.

Model serving
Governance
Guardrails
RBAC
Audit
Policy
Model Gateway

Your infrastructure

Deployment substrate

You choose the perimeter and you hold the keys inside it. Air-gapped is the base case here, not an enterprise tier bolted onto a cloud product.

Air-gapped

Your cloud tenancy

Bare metal

The Foundation is what your security team reviews. They review it once.

Explore the architecture

One platform, two applications: DocxIntel and AgentLab on Private AI Foundation, deployed air-gapped, in your cloud tenancy, or on bare metal

Industries

Private AI for industries that run on sensitive data.

From financial records and healthcare information to logistics operations, industrial systems and government data, BizfyLabs builds AI that works inside the environments where your business operates.

01, Finance

Turn sensitive financial data into governed intelligence.

Document intelligence, risk analysis, compliance workflows, customer operations and AI agents, deployed within your controlled environment. Statements, KYC packs, trade-finance paperwork and AML case files are read where they already sit.

DocxIntel structures those packs with a confidence score and a citation back to the page. AgentLab reconciles against core systems, opens and closes cases, and routes exceptions with reasoning attached, behind a named approver on consequential steps.

Customer, transaction and identification records do not leave the perimeter. There is no egress path for a compliance team to review, because none was built. You hold the keys.

Capabilities

Document AI
Risk & Analytics
Compliance
AI Agents

Discuss your use case →

Finance

Document AI
Risk & Analytics
Compliance
AI Agents

Start where the deadline already is.

A paid proof of value, 30 to 45 days, on one document type in your own environment. Success criteria agreed in writing before we begin.

Start a paid proof of value

What is BizfyLabs?

A complete private AI platform, entirely under your control

BizfyLabs is enterprise AI infrastructure for regulated industries, document intelligence and private agents running inside your own perimeter, with no external cloud dependency.

100% On-Premise

Runs in your data centre or private cloud, air-gapped. Your data never touches external servers.

You Control the Model

Open weights, Apache 2.0 and MIT only, shipped on your hardware. Not just your data, your model, under your jurisdiction.

Governance at Runtime

Policy, DLP, approvals and immutable audit in the path of every prompt. Enforced live, not reported afterwards.

Fixed Annual Cost

No per-token pricing. No per-page metering. No usage limits. One licence, one fee.

Full Stack Control

Not a wrapper, a complete platform. Model serving, gateway, governance, RBAC, audit, document intelligence and agents, included.

Arabic Native

Tuned on regional documents, including handwriting. Not an afterthought bolted onto an English model.

Ready to deploy AI you actually control?

See the full stack on one machine, disconnected from the network, processing your own documents.

Let’s Talk

The application stack

One private runtime. An application stack built around your business.

The BizfyLabs runtime gives every application the same private models, governed gateway, identity controls and audit layer, whether you're understanding documents, running agents, analysing data or building a system for a specific operation.

Explore the applications

6 modules

Document Intelligence

Understand documents and the information inside them. Extract, classify and reason over structured and unstructured documents, with grounded outputs and source-level traceability.

AI Agents

Turn intelligence into action. Deploy agents that use tools, connect to enterprise systems and execute governed workflows with human approval where required.

Knowledge Systems

Make enterprise knowledge usable. Connect documents, databases and internal knowledge into searchable, contextual and grounded intelligence.

Data & Analytics

Turn operational data into decisions. Build intelligence layers, dashboards, forecasting and decision-support systems around the data your organisation already owns.

AI Copilots

Put intelligence where people work. Build private copilots for teams, operations and specialised workflows, grounded in your organisation's data and processes.

Custom AI Systems

Build what your operation actually needs. From custom models and computer vision to intelligent enterprise applications and physical systems, engineered around the problem.

Where we differ · why sovereign matters

Your AI. Your rules.

Cloud AI platforms send the records to the model. We send the model to the records. Same words as the category, on-premise, private, governed. The difference is what you can check.

Cloud AI platforms

Their cloud regions

Document bytes and prompts leave the building for a vendor region, even when you pick “in-country”.

BizfyLabs

Your infrastructure, anywhere

Air-gapped, customer tenancy or bare metal. The runtime installs inside the perimeter you already operate.

Factor	Cloud AI platforms	BizfyLabs · private AI platform
Data location Where processing actually happens	Their cloud regions Document bytes and prompts leave the building for a vendor region, even when you pick “in-country”.	Your infrastructure, anywhere Air-gapped, customer tenancy or bare metal. The runtime installs inside the perimeter you already operate.
Data sovereignty Who can reach the model reading the records	Residency without control A regional flag answers where data sits. The intelligence layer is still operated in the vendor’s jurisdiction.	Complete control, zero egress No egress path exists. Keys, weights and audit logs stay on hardware you control.
Cost model How the bill moves	Usage-based, unpredictable Per token, per page, per call, or per seat. Your own volume becomes the invoice.	Fixed annual licence One platform fee. No per-token pricing, no per-page metering. Cost does not move when volume does.
Air-gapped operation Whether the product can run with no network	Cloud is the product Self-host is a project, if it exists. Updates and telemetry usually still call home.	Air-gapped by default No network required. Updates move by controlled transfer. Runs disconnected if compliance requires it.
The model itself What you can inspect and keep	Opaque endpoint Weights and licence stay with the vendor. “Model-agnostic” still defaults to their hosted model.	Open weights on your hardware Apache 2.0 and MIT only, shipped in the box. The licence list is published. The model is under your jurisdiction.
After the model acts What happens after intelligence is produced	Output, or external action You receive an answer, structured output or an agent action through the vendor's environment.	Action stays inside the perimeter Models, applications and agents operate on the same private runtime. Consequential actions can require a named approver and every step is auditable.
Regional intelligence Whether the system understands the environment it operates in	Global first, regional later General-purpose models often treat regional documents, language, forms and handwriting as localisation problems.	Arabic-native, region-aware Tuned on regional documents, language, forms and handwriting, with grounded outputs and citation to the source.

Factor

Cloud AI platforms

BizfyLabs · private AI platform

Data location

Where processing actually happens

Their cloud regions

Document bytes and prompts leave the building for a vendor region, even when you pick “in-country”.

Your infrastructure, anywhere

Air-gapped, customer tenancy or bare metal. The runtime installs inside the perimeter you already operate.

Data sovereignty

Who can reach the model reading the records

Residency without control

A regional flag answers where data sits. The intelligence layer is still operated in the vendor’s jurisdiction.

Complete control, zero egress

No egress path exists. Keys, weights and audit logs stay on hardware you control.

Cost model

How the bill moves

Usage-based, unpredictable

Per token, per page, per call, or per seat. Your own volume becomes the invoice.

Fixed annual licence

One platform fee. No per-token pricing, no per-page metering. Cost does not move when volume does.

Air-gapped operation

Whether the product can run with no network

Cloud is the product

Self-host is a project, if it exists. Updates and telemetry usually still call home.

Air-gapped by default

No network required. Updates move by controlled transfer. Runs disconnected if compliance requires it.

The model itself

What you can inspect and keep

Opaque endpoint

Weights and licence stay with the vendor. “Model-agnostic” still defaults to their hosted model.

Open weights on your hardware

Apache 2.0 and MIT only, shipped in the box. The licence list is published. The model is under your jurisdiction.

After the model acts

What happens after intelligence is produced

Output, or external action

You receive an answer, structured output or an agent action through the vendor's environment.

Action stays inside the perimeter

Models, applications and agents operate on the same private runtime. Consequential actions can require a named approver and every step is auditable.

Regional intelligence

Whether the system understands the environment it operates in

Global first, regional later

General-purpose models often treat regional documents, language, forms and handwriting as localisation problems.

Arabic-native, region-aware

Tuned on regional documents, language, forms and handwriting, with grounded outputs and citation to the source.

Your data, your model, your infrastructure, no third-party cloud in the path, and no accuracy figure published until test set, date, model version and method travel with it.

Read the architecture before you talk to us.

Deployment models, the model licence list and the security pack are published. Your legal team reads files, not assurances.

See how it deploys

Sovereign AI

Your data, your models, your infrastructure

A complete AI pipeline that runs inside your environment, from your data and models to production applications, with nothing leaving your control.

Step 1

Data & knowledge

Ingest, clean and structure your documents, data and enterprise knowledge, without moving them outside your environment.

Step 2

Select model

Benchmark and choose the right open-weight model for your use case, accuracy requirements and infrastructure.

Step 3

Adapt intelligence

Fine-tune, configure or train models for your domain, workflow and accuracy requirements.

Step 4

Deploy privately

Deploy on-premise, in your private cloud or completely air-gapped, inside the infrastructure you control.

Step 5

Run applications

Serve secure models, agents and AI applications inside your environment, connected to the systems your organisation already runs.

Discuss your deployment

Applications

Two applications on one runtime

Document intelligence

DocxIntel

Reads what your organisation receives, without a page leaving the building. 30+ formats, Arabic and English in the same document, including handwriting.

Analyse
Layout, structure and content across scans, phone captures, PDFs, images and office formats.
Identify
Pull named entities, dates, amounts, references and clinical or financial fields, each with a confidence score.
Classify
Sort mixed intake into document types and route by type before anyone opens it.
Map
Take fields from any document layout into your schema, claims, core banking, ERP, case management.
Modify
Redact, mask and transform. Original always preserved, every change logged.
Ask
Question a document or a set of documents in natural language, with citations back to the source region.

What makes it different

Arabic-native, tuned on regional documents rather than translated into an English pipeline. Every field carries a confidence score and a citation back to the region of the page it came from. Low-confidence fields route to a human queue rather than guessing.

Request a private demo →

DocxIntel, document intelligence that never leaves your building

Extraction

Pre-authorisation · Arabic, handwritten

1Member IDconf 0.97
2Procedure codeconf 0.94
3Diagnosisconf 0.71 → review queue

Private AI agents

AgentLab

Acts on what the documents said. Agents that reach your systems of record, on the runtime you already installed, inside the same perimeter.

Build
Describe an agent in chat, wire it on a visual canvas, or write it in code. All three produce the same artefact.
Connect
Connector catalog, MCP tools and custom APIs into systems already running inside your network.
Context
Files, knowledge bases and structured tables as the memory agents reason over.
Deploy
Private API, scheduled runs and internal chat surfaces. No public endpoint required.
Observe
Full run traces, step-level logs and complete run history. Every failure has an exact location.
Control
Approval checkpoints on consequential actions, versioned prompts and tools, rollback on exception.

What agents actually do here

Reconcile an extracted claim against the policy system. Route exceptions with reasoning attached. Draft a decision for sign-off. Open, update and close cases. Flag anomalies for review. Every action is logged, attributable and reversible. Nothing consequential executes without a named approver.

See AgentLab in action →Sign in

AgentLab, the private AI agent workspace

Custom AI

Build around the operation

From custom models and computer vision to intelligent enterprise applications and physical systems, BizfyLabs engineers AI around the problem, on the same private runtime.

Build with BizfyLabs →

Integrations

Connectors stay inside the perimeter

AgentLab talks to the systems of record you already run, MCP tools, APIs, and the suites on your own tenancy. Nothing is sent to a public agent host.

How agents connect

Published stack

What's in the box

Open-weight models for vision, language, retrieval and reasoning, shipped as files on disk, with published licences. Apache 2.0 and MIT weights only. The full model list lives on the Sovereignty page.

Vision

Image and document understanding using open-weight models you can inspect, deploy and control.

Language Models

Generation, reasoning and instruction-following inside the perimeter, behind the Model Gateway.

Embeddings

Turn enterprise content into searchable representations, stored alongside the data already inside your environment.

Reranking

Improve retrieval precision with a local second-pass ranker, no third-party ranking API required.

View model & licence list →

Deployment

Four tiers. Keys stay with the customer.

In every tier that touches customer data, the customer holds the encryption keys. Licence is a fixed annual term. Deployment is a fixed-fee package. We do not quote time-and-materials rates.

Air-gapped

No network path out. Transfer of models and licences is physical or otherwise controlled. Highest isolation.

Private cloud

Customer data centre or private cloud fabric. Foundation and applications stay inside that fabric.

Managed single-tenant

Customer tenancy in-region. We may assist with operations. We still do not hold the data. You hold the keys.

Evaluation sandbox

Isolated evaluation only. Not a production residency control. Used to decide whether an offline demo is worth scheduling.

Use cases

Start where the work already happens

Document → Decision

Turn every incoming claim into structured, reviewable data.

Ingest forms, reports, images and supporting documents, extract the information that matters, validate it against business rules and route exceptions to the right team.

What it demonstrates

Vision
Document AI
Extraction
Validation
Workflow

DocxIntel + AgentLab

Discuss your use case →

You keep the relationship. We supply the product.

Fixed-fee deployment packages you can quote directly, reference architectures, and deal registration. We do not compete with partners for services revenue.

Become a partner

FAQ

Questions we hear often

Common questions about BizfyLabs, private AI and what actually stays inside your perimeter.

Talk to an AI engineer

Inside your perimeter. Your data centre, your own cloud tenancy in-region, or isolated in-country hardware. There is no BizfyLabs-operated endpoint in the path, because none was built. Nothing calls home.

Not by default. Your data stays inside your environment. Depending on the use case, we can use retrieval, prompting, configuration, fine-tuning or model training, without sending your data to a third-party model provider.

Residency answers where the bytes sit. It does not answer who controls the model reading them. If the weights are operated by a vendor in another jurisdiction, you have residency without sovereignty, and under CBUAE and the Health ICT Law, that gap is yours to explain, not the vendor's.

Fixed annual licence, per environment for the platform, tiered by volume for application modules. No per-token pricing, no per-page metering, no usage caps. Deployment is a fixed-fee package, never quoted in man-days. Your cost does not move when your volume does.

You don't, from a marketing page, which is why we don't publish undated numbers. Every figure we release carries its test set, composition, date, model version and scoring method. The faster answer is the paid proof of value: 30 to 45 days on your own documents, in your own environment, with success criteria agreed in writing before we start.

Yes, and that is the base case rather than a hardened option. Model weights, licence text and documentation ship as files on disk. Updates arrive as signed offline bundles on your schedule. Diagnostics produce a file you inspect before it goes anywhere.

Only Apache 2.0 and MIT weights, vision and OCR, LLM, embeddings and reranking. Every component, version and licence is published, and the licence text ships on disk. An SBOM covering models as well as code is generated per release. Nothing carries a usage gate or a policy a vendor can revise after you deploy.

You do, in every tier that touches your data. In managed single-tenant deployments the infrastructure sits in our account contractually assigned to you, and the keys remain yours.

Starter configuration is 8 vCPU and 32 GB with no GPU. A GPU purchase is never a precondition for beginning. Sizing tables by hardware tier are published with the test set and date they were measured on.

We start with the business problem and constraints, then design the model, data, application and deployment architecture. We build and evaluate the system against representative workloads before deploying it inside your environment. Existing systems can be connected through APIs, databases and enterprise integrations.

Contact

Let's talk about your perimeter

Tell us the workflow and the room it has to stay in. Book here, we'll come back with a plan for an offline demo on a machine disconnected from the network. No webinar. No vendor cloud in the path.

hello@bizfylabs.com
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BizfyLabs

30 min On-site or disconnected

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September 2026

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The full stack on one machine, disconnected from the network.

In your office, on your documents, with the cable pulled out. No competitor's sales engineer can do this.

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