Why SageX
Today
Every question means going place to place, and someone reconciling what comes back.
With SageX
One question, one answer, and nothing has to move.
Today
Your data team has to get it into shape first. That is 20+ hours a week, per person.
With SageX
That work is already done.
Today
While your question gets answered, whoever runs the tool holds your files.
With SageX
Your files stay on your storage.
A better LLM does not fix any of this. It gets fixed in the foundational data layer. That is the layer we built.
Nitin spent his career building data products for large institutions - all three founders did. They met this problem on every build. SageX fixes what actually costs you weeks and months.
What it takes to see it working
Cost
$80-150KA fraction
for the pilotof a typical pilot's cost
Effort
Weeks of setupUnder 15 minutes
to get it up and running
Time to production
MonthsUnder 3 hours
before it is live in your own cloud
The founders take your questions next.
The founders
Nitin Gupta · Co-founder and CEO
You've read the page. These are the questions your own people will ask you. Pick the one on your mind - you'll get it straight.
Kiran Kumar - Co-founder and CTO
Fair reflex - and half right. An LLM is genuinely good at answering questions.
Your problem is not the answering.
It is the state of the data the question lands on - an LLM reasons over whatever you hand it, and it cannot fix what it is handed.
That fix lives a layer down, in the foundation.
Getting your data into shape was never the model's job - it is ours.
Kiran Kumar - Co-founder and CTO
If it were, you should walk away - a wrapper is one API call anyone can copy.
A wrapper takes your input, passes it to a model, and returns the output.
That is not this architecture - the work happens in the data layer underneath, and that layer is ours.
The model is the replaceable part.
Swap it next year - the foundation stays yours.
Kiran Kumar - Co-founder and CTO
A tool does one job when you open it.
A foundation works underneath every job.
Your finance system did that for your numbers - nothing did it for the contracts, filings, and reports your firm actually runs on.
The test is simple: take a tool away and tomorrow looks the same.
Take a foundation away and everything on top of it stops.
Nitin Gupta - Co-founder and CEO
You should ask - you paid for the warehouse, and it does its job.
Snowflake and Databricks solved 10 to 20% of enterprise data - the structured part.
SageX owns the 80 to 90% left behind: the contracts, filings, reports, and mail that never fit rows and tables.
Structured data got the data warehouse.
Unstructured data gets SageX. Nothing you run today moves or changes.
Nitin Gupta - Co-founder and CEO
No. And be suspicious of anything that says it does.
It sits beside the warehouse and covers what the warehouse never held.
Your pipelines, your reports, your team's work - untouched.
What changes is what a question can reach: all of your data, not just the half in tables.
Kiran Kumar - Co-founder and CTO
The mess is the point. Clean, tidy data would not need a foundation.
You do not clean anything first.
Connect a source as it is - one sample file is enough to set up the whole pipeline - and the system reads your data where it lives.
Scattered and messy is the normal starting state.
It is the state this was built for.
Kiran Kumar - Co-founder and CTO
Honestly? You could. Teams have.
The going rate is $440K-$895K, 6-8 engineers, and 6-10 months before it answers its first real question.
So the real question is not can you.
It is whether that is what your best engineers should spend the year on.
Kiran Kumar - Co-founder and CTO
It does make the first version cheaper. We will not argue that.
The expensive part starts after the first version works: keeping it correct as volumes grow, formats shift, and models change.
That is a standing team, not a sprint.
Cheaper to start is not cheaper to keep alive.
Kiran Kumar - Co-founder and CTO
It feels that way. It is usually the opposite.
Building does not make your data secure - it makes security entirely your problem to design, implement, audit, and maintain.
And every call your build makes to an outside model sends your content to a third party.
SageX runs inside your cloud, so that problem never opens.
Nitin Gupta - Co-founder and CEO
You are thinking of the last tool you sponsored. Fair.
Those months come from reviews that fire when your data has to go somewhere else.
SageX deploys inside your cloud - we do not take your data, and we do not give it to anyone.
The review that eats the quarter has nothing to review.
What is left to approve is small. Days and not weeks and months.
Nitin Gupta - Co-founder and CEO
On your storage, inside your network.
Nothing about the way you hold your files changes - the platform comes to the data, not the other way around.
And your own security team reviews the architecture before anything goes live.
Nitin Gupta - Co-founder and CEO
Fair. We would.
So do not take our word for anything on this page.
Run it on your own files and judge the answers yourself - every answer shows you where it came from.
Nothing stands between you and finding out.
That is the whole conversation - you now hold the answers your room will ask for.
Trying SageX
Rakesh Srivastava
Co-founder and COO
My co-founders told you what SageX does. Getting it running is my job.
Rakesh has run operations for twenty-five years, at CGI and 24/7.ai, without a failure. When conflict hit the Middle East, the backup plans he had written took over within hours.
live, revenue-generating deployments are running right now.
Not pilots. Production.
Rakesh Srivastava · Co-founder and COO
Bring one or two files your team already knows the answers to. Fifteen minutes later, check its answers against yours.
That leaves the work itself - who does it, and how much of it is yours.
Who does the work
SageX builds
normally the painstaking part - all of it from your own data
Your team validates
what a correct answer looks like
SageX proposes
Take a management fee. It appears in more than one place. SageX proposes where to take it from.
Your team validates
They know which one they would stand behind. They confirm it, or point it somewhere else. That is the whole of your team's part.
Then it holds
You make that call once. It carries from one fund to the next. When your source systems change, or you want something different out, you edit it. You do not build it again.
You keep the judgment. We build the rest.
That is the setup. The other question is what a week with it actually looks like.
That's the argument. The rest takes a minute.
A week with it
Today that still means opening the file and finding the sentence yourself.
Here you get the exact line, not roughly the page.
The work never took the hours.
Getting the data ready, checked and out did.
What stays yours
What counts as correct, what gets checked harder, what goes out - your team's calls, all of them. Nothing leaves without a person signing off.
Correct it once and it stays corrected - for the next file, the next fund, the next person in the seat. The work stops resetting to zero.
The old way
Every new request started from zero.
The method lived in one person's head.
The second answer never quite matched the first.
So every answer stayed partial.
Manageable for one file. Impossible for a pile of them.
Done was never the same as delivered.
Who this isn't for
If your team hasn't worked with AI yet, this isn't your next step - that conversation happens face to face.
If you already know where the work breaks, see it answer on your own data.