DigiEdze AI · Generative AI
Enterprise Generative AI Tailored for Your Business
Move beyond generic chatbots. We build grounded, secure and production-ready generative AI applications connected to your enterprise data, your permissions model and the workflows your people already use.
- LLM applications
- copilots
- enterprise search
- RAG
- document intelligence
- multimodal AI
Reference architecture
- 06Experience layer — chat, copilot, embedded UI
- 05Orchestration — prompt, tool and routing logic
- 04Retrieval — hybrid search, re-ranking, citations
- 03Knowledge — chunked, embedded, access-tagged corpus
- 02Model layer — hosted or private inference
- 01Guardrails, evaluation and observability
The Problem
Challenges with Generative AI Implementation
A general-purpose assistant that knows nothing about your business answers confidently and wrongly.
Ungrounded output cannot be audited, so regulated functions cannot adopt it.
Every team builds its own retrieval stack, and none of them share context.
What we build
Services We Tailor for You
Grounded LLM applications
Applications whose answers are traceable to enterprise sources, with citations rendered next to the claim rather than buried in a footer.
Enterprise copilots
Role-aware assistants embedded in the tools people already work in — service desk, CRM, ERP, engineering platforms.
Enterprise search
Retrieval across documents, tickets, wikis, contracts and databases that respects the same access controls as the source systems.
Document intelligence
Extraction, classification and summarisation over contracts, claims, invoices and reports, with confidence thresholds and human review paths.
Multimodal AI
Reasoning over documents, images, diagrams and scanned records where text alone is insufficient.
Evaluation harness
A golden dataset and automated scoring built alongside the application, so quality is measured before and after every change.
How it works
Technology
- Open-weight and hosted LLMs
- Vector and hybrid search
- Re-ranking models
- Structured extraction
- Guardrail frameworks
- Evaluation tooling
Our Implementations
Use Cases
Insurance
Claims handlers get policy-grounded answers with the clause cited, cutting the time spent reading wordings.
BFSI
Relationship managers query product, policy and compliance material without leaving their servicing console.
Manufacturing
Technicians query maintenance manuals and past work orders in natural language on the shop floor.
Outcomes
What We Measure
- Groundedness and citation coverage
- Task completion rate
- Time saved per transaction
- Reduction in escalation to experts
Questions
Generative AI, Answered Directly
How is this different from deploying a commercial copilot?
A commercial copilot reasons over the data its vendor can reach, under that vendor's permission model and pricing. We build systems grounded in your full estate — including systems no SaaS copilot connects to — under your access controls, with your choice of model and hosting.
How do you stop the model inventing answers?
Retrieval grounding with citations, structured refusal when evidence is weak, groundedness scoring in the evaluation harness, and confidence thresholds that route uncertain cases to a human instead of guessing.
Can generative AI run without sending data to a public model?
Yes. Open-weight models hosted inside your perimeter serve the majority of enterprise generative workloads. See Sovereign AI and Private AI for the deployment patterns.
Related services
Data & Knowledge
Enterprise RAG & Search
Access-aware retrieval over the knowledge your business runs on.
ExploreIntelligence
AI Application Development
AI capabilities embedded in the workflows your teams already use.
ExplorePlatform & Operations
AI Evaluation
Golden datasets, scorers and regression gates for AI change.
ExploreChoose your starting point
Where Are You Today?
Enterprise AI conversations stall when the entry point is wrong. Pick the sentence that matches your situation.
We have an idea.
→ AI STRATEGY
We have a POC.
→ AI PRODUCTIONIZATION
We have an AI application.
→ LLMOPS / AGENTOPS
We need autonomous workflows.
→ AGENTIC AI
Our AI is too expensive.
→ AI FINOPS
Our AI can't reach enterprise knowledge.
→ RAG & KNOWLEDGE
We can't send data to public AI.
→ SOVEREIGN AI
We need to run AI securely.
→ AI SECURITY
Build Your Enterprise Generative AI
Bring the constraint you are facing with, across data, security, cost, sovereignty, agents, or legacy systems.
30 MINUTES WITH AN ARCHITECT · BRING YOUR HARDEST CONSTRAINT