AI Consulting

Your data.
Your walls.
Your AI.

Enterprise AI that stays on your premises. Natural language interfaces to your data — no public models, no data privacy risk, no SQL required.

See How It Works
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How many consumers in the northern region are more than 3 months overdue on payments?

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Querying billing system...

4,832 consumers have outstanding balances older than 90 days. One sub-district accounts for 34% of this figure.

Answered from live billing data · On-premise Llama 3

Break it down by sub-district

Ask anything about your data...
The Problem

Management needs answers. The data has them. Nothing connects the two.

Business intelligence systems cover the reports someone thought to build. But management always needs the report nobody thought to build — the one that surfaces the exact problem happening right now.

The data is there. The answer is there. But getting to it requires a technical person, a query, a ticket, and a wait. By the time the answer arrives, the moment has passed.

And asking management to write SQL? Not a conversation worth having.

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Reports take days to arrive

Someone raises a request. A technical person writes the query. The answer is stale before it's delivered.

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Public AI models are a non-starter

Sending billing data, consumer records, or financial figures to a public API is not an option most enterprises will accept.

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Critical decisions made blind

When data is inaccessible to the people making decisions, intuition fills the gap. That's an expensive substitute.

The Architecture

Built for enterprises that can't afford to compromise.

Every component of this system is designed around one principle: your data never leaves your walls.

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Director
Asks a question in plain English via secure interface
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AI Engine
On-premise Llama 3. Converts English to SQL. Summarises the response.
On-Premise
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database
Data Layer
Billing system, ERP, or any SQL database. Queried securely through an MCP server.
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VPN-Gated Interface

The chat interface is only accessible within your network. No public endpoint. No exposure. Management accesses it like any internal tool.

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MCP Security Layer

The AI connects to your data through a security-hardened MCP server. Role-based access controls what each user can query. The AI can read — never write.

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On-Premise Llama 3

We deploy and configure an open-source Llama 3 model on your infrastructure. Your data never leaves your servers. No API calls to OpenAI, Anthropic, or anyone else.

Capability — Tested & Ready to Deploy

Natural Language BI for a
Large Utility Enterprise

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Management needed ad-hoc reports from a large billing system. Technical staff were bottlenecked. Public AI models were rejected on data privacy grounds.

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A secure, VPN-gated chat interface connected to the billing system via MCP server, powered by on-premise Llama 3. Directors ask in English. Answers arrive in seconds.

~0s
vs. Days for a Manual Report
100%
Data Stays On-Premise
Zero
SQL Knowledge Required

The Problem

A large utility enterprise had a comprehensive billing system holding years of consumer data — payment histories, outstanding balances, consumption records, geographic breakdowns. The data was all there.

But management's access to it was entirely mediated by technical staff. Every ad-hoc question — "How many consumers in district X are overdue?" — required someone to write a query, run it, format it, and deliver it. That process took hours or days. By the time the answer arrived, the conversation had moved on.

The obvious solution — connecting a public AI model — was a non-starter. Sending consumer billing data to an external API raised immediate data privacy and regulatory concerns that the enterprise was not willing to accept.

What We Built

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Secure Chat Interface
A clean, minimal interface accessible only through the corporate VPN. Management see a chat window — nothing more technical than that.
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On-Premise Llama 3
Deployed and fine-tuned on the client's own servers. The model converts natural language questions into SQL queries and summarises the results into plain English. No external API calls. Ever.
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MCP Security Server
A hardened MCP server sits between the AI and the database. It enforces read-only access, user-level permissions, and query sanitisation. The AI cannot modify data under any circumstance.
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Role-Based Access
Each user sees only what their role permits. A regional manager queries their region. A director queries the full dataset. Access is defined at the MCP layer, not the AI layer.

The Privacy Architecture

The entire system runs within the client's own infrastructure. The AI model is hosted on their servers. The MCP server is on their network. The chat interface is served internally. No query, no result, no data point ever crosses a network boundary to an external service. This is the architecture enterprises need — and the reason we built it on Llama 3 rather than a hosted model.

Results from Testing

In testing, the system answered complex multi-condition queries accurately — cross-referencing geographic data, payment histories, and consumption records in a single natural language request. Queries that previously required a technical resource and a day's wait were answered in under three seconds.

The director using it during testing described it as "the first time I've felt like the data was actually mine to use." That's the experience this system is designed to deliver.

The system is built, tested, and ready for enterprise deployment. If your organisation has data it can't easily access — we can change that.

Enterprise AI

Your executives deserve
answers, not waiting.

If your organisation has sensitive data and leaders who need faster answers — let's talk about what a private, on-premise AI deployment looks like for you.