Voice and language AI
Voice assistants, language systems and a company brain that answers from your own documents and data. Each is built on a custom RAG pipeline, so answers are drawn from your sources.
A practical delivery view
Knowledge that is hard to reach
Most of what a company knows sits in documents, tickets, emails, call recordings and people's heads. Staff search for answers that already exist, and customers wait while they do. General-purpose chat tools write fluently but know nothing about your policies, products or history. This page is for teams that want voice or language AI working from their own material: support and operations leads, knowledge-heavy functions, and research groups with more to read than time to read it.
- Support and operations teams
- Knowledge-heavy functions
- Research groups
Voice AI and NLP systems
We build voice AI and natural language processing (NLP) systems for specific jobs. A voice assistant listens, works out what the caller or user wants, and answers or acts in speech. NLP systems do the reading work: classifying messages, pulling the fields that matter out of free text, summarising long documents and finding the passage that answers a question. Each one is scoped to a defined task and checked against real examples from your business, since vocabulary and phrasing differ from one company to the next.
- Voice assistants
- Classification and extraction from free text
- Summaries and question answering
- Checked against your own examples
Custom RAG pipelines and the company brain
RAG, or retrieval-augmented generation, means the system looks up relevant passages in your material before it writes an answer. We build custom RAG pipelines: how documents are collected, split, indexed and searched is designed around your content. The company brain is the broadest version, a multi-purpose assistant trained on your company's own data, which staff can ask about policies, products, past work or procedures. We also support research work, where the job is finding, reading and summarising large volumes of source material.
- Custom RAG pipelines
- A company brain trained on your own data
- Support for research work
Inside your tools, with people in charge
An assistant is most useful inside tools people already have open, so we plan where it will sit before we build it. It should only answer from what the person asking is allowed to see, so access follows the permissions you already have. Personal information is kept out of what an AI model is given. We handle your data only with your explicit permission, follow a strict no-retention policy and never share it with third parties. Answers that carry weight, such as a commitment to a customer, stay with a person to approve.
- Placed where people already work
- Access follows your existing permissions
- Personal information kept out of the model
- A person approves answers that carry weight
What this has looked like in delivered work
Our delivered work in this area includes voice AI and NLP systems with custom RAG pipelines, a company brain trained on a company's own data, and support for research work. Language work also runs through other projects. For an Indian bank, we automated the processing of physical mandates and other money-transfer forms, reading handwritten text in Indian regional languages, with high accuracy and near-zero failures since launch. Our healthcare modules include a staff notetaker tuned to each client's medical terminology. Those results belong to those engagements and are no forecast for yours.
- Voice AI and NLP with custom RAG pipelines
- Company brain on a company's own data
- Bank forms: handwritten regional-language text
- Results belong to those engagements
Start with one set of questions
Choose one group of people and the questions they ask most: a support team, a sales desk, new joiners, a research unit. Gather the documents that hold the answers. That is enough for us to tell you whether a voice assistant, a language system or a company brain is the right first build, and what state your content needs to be in. You can also answer six questions on this website and receive a free written AI readiness report within one business day.
- One team and its most common questions
- The documents that hold the answers
- Free AI readiness report within one business day
Questions that come up
What is a company brain?
A multi-purpose assistant trained on your company's own data. Staff ask it questions in plain language and it answers from your documents and records. It is built for your organisation, so you set what it knows and who can ask it.
What is a RAG pipeline?
RAG stands for retrieval-augmented generation. Before answering, the system searches your material for relevant passages and writes its answer from them. A custom pipeline means the collecting, indexing and searching are designed around your content and the questions people ask.
Will the assistant ever give a wrong answer?
It can. Language models sometimes state things that are not in the source. Grounding answers in your documents and showing where each answer came from reduces this and makes errors easier to catch. Important answers should still be checked by a person.
How do you handle our documents and recordings?
Only with your explicit permission. We follow a strict no-retention policy and never share client data with third parties. Personal information is kept out of what an AI model is given. What the system may read is agreed with you before work starts.
Keep exploring
Let’s talk about your next step.
The workflow, the data and what needs to change.