One home for every document and data source.
Edge Reasoning is the one-stop knowledge layer for your entire organization. Drag in any document—PDFs, Word, Excel, PowerPoint, Markdown, images, even whole folders—and connect any data source, from Jira, Confluence, Notion, and Git repositories to Google Drive, SharePoint, S3, and SQL databases. West Edge AI turns it all into one structured, searchable knowledge layer that AI can analyze, connect, and reason over—returning grounded, cited answers. Run it locally, on-prem, or hybrid, with optimized local models or your own Anthropic or OpenAI models. Your data stays yours.
From raw files to grounded answers—organize, connect, and reason over your knowledge in one private platform.
PDFs, Word, Excel, PowerPoint, Markdown, text, images, spreadsheets, whole folders, even zipped archives—drop them in and they just flow into your knowledge layer. No tedious prep, no format wrangling.
If your team uses it, Edge Reasoning can ingest it: Jira, Confluence, Notion, GitHub and GitLab repos, Google Drive, SharePoint, S3, and SQL databases—kept in sync automatically, so you stop re-uploading the same files into chat tools.
Ask questions of your databases in natural language. Edge Reasoning generates transparent SQL and shows you the query, steps, and results.
Every answer is backed by your source material with citations—analysis you can trust and trace back, not hallucinations.
Run local, on-prem, or hybrid. Your data stays on your network, and you control exactly what—if anything—reaches an external model.
Edge Reasoning maps entities and relationships across your sources, so AI can reason over the connections between files, tickets, and systems—not just isolated documents.
Build a durable knowledge layer that improves over time. Stop re-uploading the same files and re-explaining context every session.
Run optimized local models (~1B–32B) for private, routine workloads, or bring your own Anthropic or OpenAI models where policy allows. No lock-in.
Shape domain-specific analysis, summaries, and briefing pipelines—tailored to how your team actually works with its knowledge.
From scattered data to grounded answers in five steps.
Drag and drop any document or folder, or connect any source—Jira, Confluence, Notion, Git repos, Google Drive, SharePoint, S3, and SQL databases. One place for everything your team knows.
Edge Reasoning parses your documents, code, and records—extracting concepts, entities, and relationships into a structured, provenance-tracked knowledge layer.
Deploy local, on-prem, or hybrid. Pick optimized local models for private workloads, or bring your own Anthropic or OpenAI models where policy allows.
Get grounded answers, cross-document analysis, summaries, and natural-language analytics over your databases—each with citations back to the source.
Knowledge persists and improves over time. Browse it through a wiki-style UI and graph views, and expose it to people and AI agents via API and MCP.
The research community keeps surfacing the same lessons we build on: grounded retrieval, knowledge graphs, small-model efficiency, and private, local-first AI.
"Small, well-trained models often outperform much larger models on agentic tasks, showing that scale alone is not the path to autonomy."
"Systems improve most when they can draw on a durable memory of past work. A persistent knowledge layer, not just model size, is the real driver of long-term reasoning."
"Retrieval-grounded systems produce more accurate, verifiable answers than the model alone. Connecting AI to trusted sources is what makes its reasoning reliable."
"Tiny models with recursive reasoning can outperform models hundreds of times larger on structured logic tasks—efficiency beats scale."
"Centralized AI architectures risk undermining autonomy. Distributed, local systems better preserve human agency and trust."
"Representing knowledge as a graph of entities and relationships lets models reason across documents and systems, surfacing connections that flat search misses."
Start free, keep your data local, and scale as your knowledge layer grows.
For evaluation, prototypes, and early pilots
For teams building a private knowledge layer on-prem
For regulated environments and larger deployments
Everything you need to know about private AI data reasoning.
Whether you’re centralizing scattered project knowledge, analyzing databases in plain language, or keeping sensitive data on-prem—our team will help you get started.
Questions? Reach out to our team:
contact@westedge.io