FictionEngine
A writing platform whose AI remembers your characters, scenes and voice from one session to the next.
Read the case studyPrivate AI Models
RAG Systems & Knowledge Assistants
Retrieval-augmented generation that grounds AI in your documents and data, so answers are current and point to their sources.
A language model on its own answers from memory, and its memory can be wrong or out of date. Retrieval-augmented generation (RAG) has the model look things up in your own material first, then answer with references.
We build the pipeline end to end: ingesting your documents, indexing them, retrieving the right passages, and showing people exactly where each answer came from. It can run fully inside your network.
What we do
Document ingestion
Connectors for file shares, wikis, ticketing systems and databases, kept in sync as content changes.
Search and retrieval
Hybrid keyword and semantic search tuned on your own questions.
Cited answers
Every answer links back to the passages it used, so people can check it.
Permissions
Users only see answers drawn from documents they are allowed to read.
Is this a fit?
Good for organizations with years of documents that people struggle to search, and for support teams answering the same questions every day.
Related work
Where we have done this before
Related services
Keep exploring
Pillar 02
Private AI Models
Custom models trained on your data and run inside your own walls. Your prompts, documents and answers stay on infrastructure you control.
Private AI
Custom AI Development
AI applications designed around your data and your workflow: assistants, agents, search and document processing.
Private AI
Custom AI Training & Fine-Tuning
Models fine-tuned or trained on your own data, so the AI understands your language, your documents and your field.
Tell us what you are working on.
A 30-minute call is the fastest way to find out whether we can help. You will talk to Adam directly, and you will leave with a clear next step either way.