Private AI Knowledge System for mid-market teams
Your AI pilot stalled. Put a private knowledge system into production.
We build question answering over your approved documents, with citations, permissions and evaluation, running inside your security boundary. Built for professional services, manufacturing and distribution teams. Engineering discipline, not another demo.
Fixed-scope pricing, quoted after a 30-minute readiness call.
Why pilots stall
The model is rarely the problem.
Pilots stall on the work around the model. That work is engineering, and it is where we spend our time.
Fragmented data
Documents sit across drives, inboxes and tools, in different formats and versions. The pilot worked on a clean folder. Production does not have one.
No permissions model
A demo can see everything. A production system must respect who is allowed to see what, or security will rightly stop it.
No evaluation
Nobody defined what a good answer looks like, so nobody can say whether the system is improving or quietly getting worse.
No owner
The pilot belonged to a project team. Once it ends, nobody owns the content, the quality or the next change.
What we deliver
A knowledge layer your security team can sign off.
- Private retrieval over your approved documents
- Citation-backed answers, so every answer can be checked
- Permission-aware retrieval that respects who can see what
- Deployment inside your security boundary
- Ingestion pipelines for your documents and policies
Outcome proof
What this looks like in production.
Professional Services
Company knowledge partners can find and trust
A consulting firm made past work and approved methods easy to search, with clear sources and owners for every answer.
Read the case study- 28% faster
- Proposal prep time
- 100%
- Answers with sources
How an engagement runs
Discover, build, production, extend.
- 01
Discover
We start with the AI Operations Blueprint: the sources, the users, the permissions and what a good answer means for your team.
- 02
Build
We build the ingestion, retrieval and answer layers against your real documents, with evaluation in place from the start.
- 03
Production
We deploy inside your environment, hand over runbooks, and agree who owns content and quality.
- 04
Extend
Once the knowledge layer is trusted, we extend it into agents and workflow automation.
A Starter build takes about 8 weeks, with a first working version on your documents in about 4. Fixed-scope pricing, quoted after a 30-minute readiness call. Larger programs are scoped after a discovery call.
The first step is the AI Operations Blueprint.
Working with a US team
Calls in your time zone.
We schedule calls in your time zone. Expect 4 to 6 hours of overlap with US Eastern time each working day.
Security
How we handle your data.
Systems run inside your security boundary, retrieval respects who can see what, and every answer cites its source. Read how we handle data, access, NDAs and ownership on oursecurity page.
Who is behind it
Built by engineers who have shipped production systems.
You work with the founders who scope and build the system.
Vineet Sagar
Founder & CEO
IIT Bombay alumnus with over two decades of experience building scalable tech solutions across web, mobile and enterprise systems. Leads cross-functional teams that move fast without compromising on quality.
Imran Javed
Founder & CTO
Over 15 years in software development across mobile, web and enterprise applications, with a strong foundation in full-stack engineering and solution architecture. Has led large-scale digital transformation projects.
FAQ
Questions teams ask before a call.
What is a private AI knowledge system?
It turns your policies, manuals and internal files into a searchable layer your team can ask questions of. Answers are grounded in approved sources and show where they came from.
Where does it run?
Inside your security boundary. We deploy in your infrastructure so sensitive material stays where it already lives.
How does it handle who can see what?
Retrieval is permission-aware. The system only draws on documents the person asking is allowed to see.
How do you know the answers are right?
Every answer cites its sources, and we set up evaluation as part of the build so quality can be measured and tracked over time, not judged by feel.
We already have a pilot. Do we start over?
Not necessarily. The readiness call looks at what you have, where it stalled and what is needed to run it in production. We will tell you honestly whether to extend it or rebuild.
Can it grow into agents and automation?
Yes. A trusted knowledge layer is a sound base for internal assistants, agents and workflow automation, and we can extend into those when you are ready.
Production readiness call
Tell us where your pilot stands.
A few details help us make the call useful. We will follow up to schedule it.
Prefer to talk first? Email hello@intertwinetechnologies.comor call +91 9307991901.