SIRAJ سراج
Siraj · the forward-deployed engineer for every business

Tell it the problem.
It ships the fix.

Siraj is an AI forward-deployed engineer. Say what's wrong in plain language. It investigates your data, builds the fix, ships it once you approve, and proves the number moved.

The largest companies in the world hire people to do this. Siraj does it for everyone else, and gets sharper at every business it works in.

Siraj · Almasar Distribution · Engagement 001 Demo data
Problem · as you said it
"Our deliveries keep running late."
Investigated Built Backtested Deployed Measuring · day 14
Activity
00:02connected orders db · driver logs · route sheets (read-only)
00:41analysed 4,112 delivery records across 90 days
00:44finding: 68% of late runs share the 10:00–11:30 dispatch window
01:15built staggered dispatch scheduler · backtest: 31% → 13% projected
01:16deployed with your approval
14 dmeasuring live · late rate tracking at 12%
KPI · late delivery rate
31% 12%
deployed 30% 20% 10% ● KPI verified · before / after
Start anywhere

Say it the way you'd say it out loud.

Tap one and it starts your demo request below. No spec. No ticket. Just the problem.

01 · Investigate

It doesn't ask what's wrong. It finds out.

Consultants interview you. Dashboards wait for you. Siraj goes into your actual data: orders, logs, spreadsheets, whatever you run. It comes back with the cause, not a survey of symptoms.

Your database, spreadsheets, and systems.
Not a questionnaire.

Finding · confidence 0.91
68% of late runs share one dispatch window.
10:00–11:30 08:00 16:00
4,112 delivery records · 90 days · read-only
Hypothesis
Batch release at 10:00 floods the loading bay.
The bottleneck is the queue, not the routes.
02 · Build & backtest

It writes the fix. Then proves it on your history first.

Siraj ships working software, not slides. Every fix is replayed against your own past data before it ever touches production, so you see the projected result before anything changes.

90 days replayed. 12 edge cases flagged.
Before a single live order moved.

dispatch_scheduler.py · new
def release_orders(batch):
+  slots = stagger(batch, window="20min",
+                 capacity=bay.max_load)
+  for slot in slots:
+    dispatch(slot, notify=drivers)
    log.release(batch.id)
Backtest · 90 days replayed
31% 13%
projected late rate · 12 edge cases flagged for review
03 · Deploy

You stay in command. Nothing ships without a yes.

Before anything goes live, Siraj shows you exactly what changes, in plain language: what it touches, what it expects to happen, and how to roll it back. You approve. Then it ships.

Plain language in.
Plain language before anything goes out.

Awaiting your approval
Stagger dispatch into 20-minute release slots
Changes: order release timing only, routes untouched Touches: dispatch sheet + driver notifications Expected: late rate 31% → ~13% within two weeks Rollback: one click, reverts to batch release
Approve deploy Request changes
04 · Measure

It reports in one language: the number.

Every fix names the KPI it intends to move. Then the KPI gets measured, before and after. The number decides whether it worked, not the demo. No engagement closes on an opinion.

Accountable to a measured KPI.
Every time, in writing.

Measured · day 14
31% 12%
● KPI verified · before / after
Shared layer · patterns, never data
Queue congestion at batch releaseabstracted · v3
Reorder-point driftabstracted · v1
Invoice follow-up decayabstracted · v2
How an engagement runs

Problem in. Measured result out.

01

Connect

Read-only access to what you already run. No migration, no new system to learn.

02

Investigate

Siraj works your data like an engineer on site and finds what's actually broken.

03

Build & backtest

It writes the fix and proves it against your own history before production.

04

Deploy

Ships with your explicit approval. You see every change in plain language first.

05

Measure

The promised KPI is tracked before and after. The number decides.

06

Learn

Patterns are abstracted into a shared layer. No client data ever crosses clients.

The experience layer

The agent that has solved a thousand businesses is not the same agent.

Every engagement ends with a pattern, not a file: the shape of the problem, the fix that moved the number, the failure that didn't. That pattern goes into a layer every future engagement starts from. Deployment one thousand begins where nine hundred and ninety-nine finished.

engagement 001 engagement n starts from zero starts from everything before it WHAT THE AGENT ALREADY KNOWS WHEN IT WALKS IN
Illustrative · the mechanism, not a measurement

What crosses between businesses

  • The shape of a problem
  • The fix that moved the number
  • The approach that failed, and why
  • How to tell the two apart early

What never crosses

  • Your records, in any form
  • Your customers
  • Your numbers
  • Anything that identifies you
What we're betting on

Four bets. The whole company follows from them.

01

Every business needs a forward-deployed engineer.

Not a dashboard and not a consultant. Someone who comes in, learns how the business actually works, and builds the thing that fixes it. Palantir proved that model is worth enormous money. It has stayed pointed at governments and the largest enterprises in the world, which leaves almost every other business without it.

02

That engineer can be an agent.

Investigate the data, form a hypothesis, kill it if it's wrong, write the fix, prove it on history, ship it, measure it. That loop is now something software can run end to end. Agents make the work possible at a price the other 99% of businesses can actually pay.

03

Models commoditise. Experience doesn't.

Every month the frontier models get cheaper and better, and every month that is true for everyone equally. Raw intelligence is not a moat. What separates a good forward-deployed engineer from a great one was never IQ. It's having seen the problem before. We are building for the world where the model is free and the experience is the product.

04

Experience compounds, and compounding is unstoppable.

Every deployment teaches the agent something it carries into the next business, in a different industry, in a different country. The gap doesn't hold steady. It widens on its own, and it widens fastest for whoever started first. That is the only kind of lead worth having.

Why now
Everyone is scaling human forward-deployed engineers. Humans don't scale down to the millions of businesses that could never hire one. Siraj is built for exactly those.
Demo access · pilots open

Bring us a real problem.

We're running early pilots with a small number of businesses. Tell us the thing you've given up on fixing. That's usually where we start.

We read every request ourselves and reply to the ones we can genuinely help.

Request received.
We read every one. If your problem fits an early pilot, you'll hear from us directly.