Private Knowledge Base
Your internal documents, procedures, manuals, and operational knowledge are indexed in a controlled environment, so users can ask questions and receive answers based on approved company sources.
AI Assistant
Private AI for operations teams
At NovaSets, we build local AI systems that turn your company knowledge into a secure, governed assistant for your own organization.
Local AI System
Turn company knowledge into a governed assistant
Most companies already have the information they need, but it is scattered across documents, procedures, supplier manuals, links, spreadsheets, systems, and the knowledge of key people. A generic AI tool does not know which source is approved, which terminology is correct, or which document reflects the current way of working.
From scattered knowledge to controlled AI
We bring that knowledge together in a private AI environment where your teams can upload documents, add trusted external links, manage business terminology, review feedback, and control what becomes part of the live knowledge base.
Five key areas
What we build into the system
Semantic Control
Every company has its own language. You can manage terms, aliases, site names, product names, metrics, and business definitions, so the AI understands how your organization actually speaks and works.
Document & Link Governance
Users can upload documents and add trusted external sources, but new knowledge does not automatically influence the assistant. It first passes through approval, publishing, and indexing workflows.
Evidence-Based Answers
The assistant is designed to answer from available evidence, not from guesswork. When information is missing or not approved, it should say so instead of inventing an answer.
Continuous Improvement
Feedback, review queues, semantic updates, document governance, and future impact-preview tools allow the system to improve over time without losing control.
AI aligned with your business
This creates an AI assistant that is not just intelligent, but aligned with your business, your terminology, your documents, and your rules.
The result is a practical local AI system that helps teams find knowledge faster, reduce repeated questions, preserve expertise, improve consistency, and make better decisions based on approved information.
Challenge
Knowledge scattered across systems and people
Operational knowledge often lives in ERP screens, maintenance notes, SOP folders, dashboards, email threads, and the heads of experienced colleagues. That makes answers slow, inconsistent, and dependent on who happens to be available.
3.5
Hours lost per shift searching
Teams often lose valuable time switching between systems, files, and colleagues to answer practical process questions.
40%
Improvement lost to slow answers
When answers arrive late or differ per person, execution slows and operational follow-through weakens.
70%
Of process rules stay tacit
A large share of operational know-how remains undocumented and therefore unavailable when teams need it most.
AI value
Operational knowledge becomes a private asset
A private assistant turns fragmented knowledge into a reusable company capability. Instead of repeatedly searching, asking around, or waiting for experts, teams get one place to ask operational questions and receive grounded answers.
Framework
Build operational AI in four phases
From the first workflow map to a grounded assistant in production, each phase reduces risk and creates usable results.
Phase 1
Map the workflows where answers matter most
Identify the recurring decisions, process questions, and knowledge gaps that slow your team down every day.
Phase 2
Upload company specific documents and upload links to external documents
Capture SOPs, process rules, exceptions, and expert know-how in a structure the assistant can use.
Phase 3
Connect the systems your people already use
Bring together documents, dashboards, tickets, and key applications without exposing your data publicly.
Phase 4
Refine answers with real process feedback
Improve relevance, guardrails, and trust by learning from live questions and operational review.
Use cases
The assistant answers the questions your teams ask every day
Use one assistant across production, logistics, maintenance, and support teams so operational knowledge becomes available in the moment of work.
Find the right procedure instantly
Surface the correct instruction, checklist, or process rule without browsing through folders or asking around.
Get consistent guidance when shifts change
Keep answers stable across teams, locations, and experience levels so work continues with less variation.
Answer maintenance knowledge faster
Help technicians find recurring fixes, equipment notes, and prior solutions without long search time.
Help new hires learn without waiting
Give newer colleagues a safe first layer for operational questions while reducing interruptions for senior staff.
Ready to build operational AI?
Book a short discovery session. We will translate your operational reality into a grounded AI starting point.
Questions
Straightforward answers about scope, systems, implementation, and effort.
Does this use our own data?
Yes. The assistant is built around your internal documents, process rules, workflows, and selected systems. The goal is not generic AI output, but grounded answers based on your operational context.
We already use systems, so why would we need this?
Most companies already have the data, but not one place where people can ask practical operational questions across those sources. The assistant sits above scattered systems and makes knowledge easier to use in daily work.
Can we connect the assistant to our current tools?
Yes. We can work with documents first, then connect selected systems where needed. The rollout can be phased so value starts early without waiting for a full integration programme.
How long does a first version take?
A first focused version can usually be scoped quickly once the workflow, answer scope, and knowledge sources are clear. We recommend starting narrow and improving from live use.
Do I need engineers on my side?
Not necessarily. Many first versions begin with process owners, subject matter experts, and existing documentation. Technical involvement can be added later when broader integrations are needed.
Start building operational AI
Book a short working session and we will define the workflow, answer scope, and best starting point for your private assistant.
Prefer a direct conversation? Book a call and we will guide you through the options.