Large Language Models are revolutionising how companies leverage their intellectual property. But off-the-shelf public chatbots do not know your files, proprietary rate cards, or operational history.
Domain-Specific
index PDFs, Word, Excel, emails, and databases
100% Private
secure cloud deployment in your private tenant
Model Agnostic
swap between Claude, Gemini, and open models
4hr Drafts
document cycle turnaround compressed from days
Foundation models are powerful, but deploying standard commercial instances without boundaries exposes businesses to accuracy, security, and financial risks.
01
Commercial models generate answers from public general internet corpora. They fail to understand specialised company terminology or precise domain formulas, producing misleading outputs.
02
Sending sensitive client contracts, financial reports, or internal manuals to public commercial chatbots risks exposure to data leaks and feeds proprietary knowledge to third-party models.
03
Interrogating massive datasets via public pay-per-token models results in high, unpredictable API costs. Standard platforms do not offer targeted token minimization.
At Brainpool, we configure and fine-tune Large Language Models (LLMs) to fit narrow, domain-specific business parameters safely.
Safely ingest unstructured data from emails, presentations, PDFs, Excel sheets, and handwritten notes into a secure document vector space.
Zero-risk corporate privacy
Full contextual background mapping
Perform deep semantic searches across your database to retrieve highly relevant business intelligence and project histories instantly.
Accurate facts with direct source citations
Bypass folders and fragmented email chains
Synthesise highly specific findings, summaries, and branded business reports based solely on your own uploaded proprietary sources.
Structured report templates
Consistent corporate branding limits admin drag
Utilise specialised retrieval plugins and hyper-personalised prompt templates to only pull the exact context needed for each request.
Saves up to 70% in model compute fees
Fast, low-latency agentic responses
Provide your team with direct, precise answers compiled across centuries of aggregated files. Ask natural language questions like:
"In the last 20 years, how many times have we spoken to this client?"
"What is the total advertising spend on this product line since 2011?"
"Make comparison between company X and company Y based on Z?"
"List every time person X is mentioned in documentation?"
"How many investments did X make in Y in the past Z years?"
"What would X person do in this situation?"
Rather than building a brittle integration tied to one provider, Brainpool engineers a flexible RAG platform that easily handles model generation, parameter tuning, and strict tenant security.
Large Language Models are designed to understand and generate human-like text by training on billions of words. While foundation models excel at open-domain conversation, they require strict fine-tuning, system prompting constraints, and local sandboxing before handling client-facing operations safely.
We begin every Custom GPT engagement with an AI Strategy assessment to analyse feasibility, recommend optimal hosting bounds, and layout structured compute targets.
PIPELINE STRUCTURE:
Ingest unstructured documents (PDF, Excel, hand-written notes)
Apply semantic chunking and high-accuracy embedding calculations
Store index in secure local Vector DB (Zero general model training leak)
Inject exact context citations into mathematical user prompts
status: active · deployed in private tenant
Who we work with
Get in touch with us now to book your first Artificial Intelligence consultation and discuss how Brainpool can develop your custom GPT solution on our Cortex platform.
Phase I — Feasibility diagnostic & security audit
Phase II — Working Proof of Concept against real files (2-3 months)
Phase III — Secure cloud sandbox deployment to production
Cross the GenAI Divide. Own your AI.