Retrieval that makes answers traceable
Document ingestion, chunking, embeddings and a retrieval layer tuned on your own content, so every answer can be traced to a source.
2 wks
To a working POC
15
AI capabilities we build
9
Years in business
What you get
What every RAG build includes
Retrieval decides the quality. We spend the time on how your documents are split, indexed and found.
Talk through the use caseChunking and embedding strategy tuned to your documents
Retrieval quality measured, not assumed
Source citations surfaced to the user
Our process
Four steps from documents to dependable answers
Good retrieval is tested, not assumed.
- 01
Audit the documents
Formats, quality, duplicates and what changes often.
- 02
Design retrieval
Chunking, embeddings, search and re-ranking tuned on your questions.
- 03
Build the pipeline
Ingestion that stays up to date, answers with sources, and permissions respected.
- 04
Evaluate retrieval & answers
Whether the right passage is found, and whether the answer uses it correctly.
Tech stack
What we build it with
Four layers, each chosen per project. Open one to see what sits in it and why.
Models & frameworks
The layer that generates. Chosen per task against quality, latency and cost.
Retrieval & data
Where grounded answers come from: your documents, indexed and tuned.
Serving & ops
How it runs in production, and how you see what it is doing.
Evaluation
How we know the output is good enough before a user sees it.
More AI capabilities
Fourteen more ways we apply AI
AI Software Development
End-to-end AI product builds.
AI Chatbot Development
Smart, conversational AI for business.
AI Agents Development
Linked agents for smarter tasks.
AI Voice Agents
Voice intake and call handling.
Generative AI Solutions
AI that creates and innovates.
LLM Chatbot Development
Grounded in your own content.
LLMs for SMEs & Enterprises
AI built to scale with you.
GPT Integration
AI seamlessly in your workflow.
Prompt Engineering
Better prompts, better results.
Machine Learning Development
AI that learns from your data.
NLP Development
Classification, extraction, sentiment.
AI Workflow Automation
Process automation that holds up.
AI MVPs & POCs
Proof before you commit to a build.
AI Consulting
Where AI pays off, and where it doesn't.
Frequently asked questions
The questions we get asked about AI
Data handling, output quality, cost and ownership.
Start with the documents people search most
Two weeks, your documents, a working question-and-answer system and a retrieval score.