Problems this solves

Staff spend hours searching manuals, policies or archives for answers that already exist.
PDFs, scans and forms are re-typed by hand before anyone can use the data.
You want an AI assistant, but need answers grounded in your documents — with sources.
An AI prototype works in a demo but fails, slows down or breaks in production.

What we build

Each solution is built around your own documents, data and processes, and delivered as working software — not a slide deck.

Service	What it is	Example use
Custom AI chatbot	A chatbot tailored to your business information and workflows, helping users find answers and complete common tasks.	Website assistant, FAQ bot or internal employee assistant.
Document knowledge assistant (RAG)	An AI assistant that retrieves information from your documents and generates answers with references to the supporting sources.	Ask questions about policies, manuals, research papers or company documentation.
Semantic & hybrid search	Search that combines meaning-based retrieval with keyword search and filters to help users find relevant information.	Search research articles, legal documents, product catalogs or internal knowledge.
AI document processing & OCR	A pipeline that extracts text and structured fields from PDFs, scanned documents and images for further processing.	Convert reports, forms or scanned records into searchable data or JSON.
Information extraction & entity recognition	Extract specific entities and relationships from large amounts of text using rules, language models or a combined approach.	Identify drug names, adverse reactions, ages, organizations or document references.
Automated research & data collection	A system that gathers information from public sources and APIs, cleans it and prepares it for analysis or search.	Literature monitoring, research databases or business information collection.
AI summarization & text processing	Tools that turn lengthy or noisy text into concise summaries, structured outputs or standardized questions.	Summarize articles, simplify support requests or organize document collections.
Data ingestion & vector database pipelines	Reliable workflows that process, split, embed and store documents for AI retrieval and search.	Connect an existing document database to Weaviate and keep its search content up to date.
Business workflow automation	Software that connects processing steps and automates repetitive work through APIs, background tasks and queues.	Process uploaded files, enrich records, generate outputs and track job status automatically.
Custom APIs & backend services	Backend applications that connect AI models, databases and external services through documented API endpoints.	Add AI search, document analysis or prediction capabilities to an existing application.
Local & self-hosted AI integration	Language models running on your own infrastructure, with the model chosen to fit your hardware and task.	Run document extraction or summarization with Ollama and smaller language models.
AI model evaluation & optimization	Compare models using task-specific datasets, quality metrics, response times and resource usage.	Choose a suitable model for extraction or summarization and track its performance with MLflow.
Machine learning prediction services	Build or integrate models for structured data, including preprocessing, missing-value handling, evaluation and API access.	Classification, risk scoring or other prediction tasks backed by suitable training data.
AI deployment & troubleshooting	Package AI services with Docker and investigate failures across APIs, background workers, model calls and databases.	Resolve ingestion failures, slow processing, connection errors or deployment problems.

Specialized solutions

Research and literature assistant. Collect, process, search and summarize scientific publications, with structured extraction of the information that matters to your research question.

Legal document search assistant. Search judgments and acts using semantic retrieval, metadata filters and results linked back to the source documents.

Medical AI research prototype. Document extraction, medical text analysis or prediction workflows for research and evaluation. These are research tools: any clinical use requires separate validation.

Ways to work with us

Proof of concept. A focused prototype that tests an idea on a sample of your data, so you can see whether it works before committing to a full build.

Custom implementation. An end-to-end solution with agreed features, integrations, deployment and documentation.

Existing system improvement. Debugging, evaluation or extension of an AI application or data pipeline you already run.

How we keep AI tools trustworthy

Language models can produce confident answers that are wrong. We design for that rather than hoping it won't happen:

Answers grounded in your sources. Knowledge assistants cite the documents they used, so people can check them.
Measured, not assumed. We evaluate models on examples from your own tasks — quality, speed and cost — before recommending one.
Your data stays where it needs to. When documents can't leave your infrastructure, we use self-hosted models instead of external APIs.
Built to run, not just to demo. Services are containerized, logged and documented, with clear handling for failures and retries.

What's included

Custom AI chatbots
Document knowledge assistants (RAG) with source references
Semantic and hybrid search
AI document processing and OCR
Information extraction and entity recognition
Automated research and data collection
AI summarization and text processing
Data ingestion and vector database pipelines
Business workflow automation
Custom APIs and backend services
Local and self-hosted AI integration
AI model evaluation and optimization
Machine learning prediction services
AI deployment and troubleshooting

How it works

Agree the use case, the data involved and how success will be measured.
Build a focused proof of concept on a sample of your data.
Evaluate quality, speed and running cost against your real tasks.
Implement, deploy and document the solution — or improve the system you already have.

Not sure where to start? Tell us about your data and what you want to achieve. We'll suggest the smallest useful first step — often a focused proof of concept.

Discuss an AI Project

AI & Software Development