AI for the Systems and Data You Already Have
We focus on two things: adding AI to existing business systems without a rebuild, and turning scattered data into forecasts and answers. Below the two offers sit the AI capabilities that power them. We build AI systems around real business data and workflows. Our work includes multi-LLM applications, RAG knowledge assistants, natural-language database querying, OCR and document extraction, dashboards, role-based administration and API integration. The goal is not to add AI for its own sake, but to combine models, software and data in a controlled system that users can trust and operate.
Two offers, one goal: smarter systems and data
AI Modernization of Legacy Systems
Add AI features to your existing ERP, CRM, banking, insurance or manufacturing software without a full rebuild.
- Document processing
- Intelligent search
- Chatbots on internal data
- Predictive maintenance
- Automated reporting
- Code and legacy migration assistance
AI-Powered Data Analytics
Clean up scattered data, build dashboards, then add forecasting, anomaly detection and natural-language querying.
- Demand forecasting
- Churn prediction
- Fraud detection
- Customer segmentation
- Anomaly detection
- Natural-language querying: “ask your data”
Prove the value before you commit to the build
AI projects stall when buyers fear wasted spend. So we start small, with fixed-price packages and a clear decision point after each stage.
- 1–2 weeks · Fixed price
AI Readiness Audit
We review your systems and data, then deliver a ranked list of AI use cases with estimated ROI.
- 3–6 weeks · Fixed price
Proof of Concept
One working use case built on your real data, so you see results before you commit to scale.
- Ongoing
Scale-Up Contract
Production rollout, integration with your systems, monitoring and ongoing support.
AI Capabilities We Build With
The building blocks behind both offers.
Generative AI Development
AI Agent Development
RAG & Enterprise Search
LLM Integration
AI Chatbots & Copilots
Intelligent Document Processing
AI Automation
AI Consulting & Readiness
Data Engineering for AI
Vector Search Development
AI Use Cases
Private knowledge assistants over company documents
Natural-language querying of business databases
Legal and professional information search
Document extraction from invoices, receipts, business cards, IDs, cheques and forms
Catalogue and list matching with human verification
Charts and dashboards generated from plain-language questions
External application integration through APIs
AI Engineering Architecture
- Frontend application or external client
- Python/Flask backend and business logic
- LangChain orchestration for prompts, models and tool calls
- Multi-LLM layer with OpenAI, Gemini, Claude, Llama, DeepSeek, Mistral and other supported models
- Weaviate vector database for semantic retrieval
- Relational and operational data sources
- Role-based access, usage tracking and API authentication
Responsible & Production AI
- Access permissions and role separation
- Private knowledge collections per bot/group in MultiLLM AI Platform
- Controlled database access so only allowed tables/results are used
- Token and budget limits
- HTTPS and token-authenticated API communication
- Human-in-the-loop verification for accuracy-sensitive extraction workflows
- Model selection based on the use case, cost and complexity
Discuss an AI Use Case
Start with one workflow, dataset or document process. We can help validate value, design the architecture and move from proof of concept to a production integration.