Manifest
๐Ÿ”ฅ 0 LAUNCH SUBSCRIBERS
SYSTEM ACTIVE
SIMULATED
NO LIVE
API CALLS

Every listing
starts as a manifest.

Trend, supplier, price, and risk, computed automatically, checked by a person, before anything ships.

TRACKING ยท AUTONOMOUS-PIPELINE-V1 ยท STATUS: OPERATIONAL
ENGINEERING STACK: Python 3.11 SQLAlchemy ORM XGBoost ML Multi-LLM Synthesis Thompson Sampling Telegram Bot API
TRENDS SCANNED --
/
LISTINGS CREATED --
/
ORDERS (30D) --
/
RTO RATE --%
/
STATUS OPERATIONAL

Watch it run

Type a product idea and step through the real pipeline logic, using the same pricing and risk formulas the live system runs, computed entirely in your browser. No server call, no AI provider, nothing to wait on.

SAMPLE PRESETS:
Trend match
Supplier match
Listing copy
Price floor
Risk score
Reviewer queue
simulation.log
[system] enter product query above & click 'Run simulation'
Awaiting input
โ€”
MFT-000000000
WHOLESALEโ€”
PRICE FLOORโ€”
RTO RISKโ€”
STATUSโ€”

Simulated client-side only. No data leaves your browser, no AI provider is called, and no listing is created anywhere.

Manual labor vs Manifest engine

โŒ MANUAL DROPSHIPPING
  • 3+ hours/day spent copying titles, descriptions & photos manually
  • High risk of negative-margin sales from hidden GST & shipping fees
  • High RTO return rates (18-30%) burning cash on failed COD deliveries
  • Juggling 5 supplier portals and messy manual spreadsheets
โšก WITH MANIFEST ENGINE
  • 0 manual hours โ€” continuous automated trend-to-catalog pipeline
  • 1.35x Min Margin Floor mathematically enforced on every listing
  • XGBoost ML Risk Model flags high-risk pincodes before shipping
  • 1-Tap Telegram review on your phone over morning coffee

How a listing gets built

STEP01

Trend match

Scans live trend sources for rising product concepts, with a ranked fallback chain if any source fails.

LIVE SOURCE
STEP02

Supplier match

Checked against multiple supplier catalogs through one common unified gateway.

MULTI-VENDOR
STEP03

Listing copy

Synthesizes AI copywriting with multi-provider debate and deterministic fallback guards.

AI SYNTHESIS
STEP04

Price floor

Priced by a reinforcement-learning model, constrained by a real cost floor it can't go below.

MARGIN SAFE
STEP05

Risk score

Evaluates pincode return-to-origin risk and brand copyright compliance via XGBoost ML.

XGBOOST ML
STEP06

Human review

Sent to a person for one-tap approval. Nothing publishes without an explicit human decision.

โœˆ๏ธ TELEGRAM BOT SIMULATOR INTERACTIVE
TEST BOT COMMAND:

๐Ÿ“ฆ NEW LISTING READY FOR APPROVAL
Item: Sunset Lamp RGB Atmosphere Light
Wholesale: โ‚น180 | Target Price: โ‚น599 | RTO Risk: 14.2% (LOW)

โœ… Approve & Generate CSV โŒ Reject Listing
REQUIRED

A day in the life of a solo founder

09:00 AM IST

AUTOMATED SCAN

Engine scans search & marketplace feeds while you sleep.

โž”
09:05 AM IST

AI SYNTHESIS & MARGIN

Computes 1.35x margin floor & synthesizes listing copy.

โž”
09:10 AM IST

XGBOOST RTO RISK

ML model scores pincode risk & filters out high-loss items.

โž”
09:11 AM IST

1-TAP TELEGRAM APPROVAL

You tap [โœ… Approve] on your phone over morning coffee. Done.

Test the XGBoost Pincode RTO Risk Predictor

Type an Indian pincode to evaluate return-to-origin loss probability in real time.

Delhi (110001) Mumbai (400001) Patna (800001) Bengaluru (560001)
PINCODE REGION: Delhi NCR (North Zone)
ESTIMATED RTO RISK: 8.4% (LOW RISK)
FULFILLMENT DECISION: โœ… APPROVED FOR COD & PREPAID

Calculate your automation ROI

Estimate hours saved and RTO losses prevented when running Manifest autonomously.

DAILY ORDERS TARGET 30 orders/day
AVG ORDER VALUE (AOV) โ‚น699
EST. TIME SAVED / MO 37.5 hrs Automated cataloging & pricing
RTO LOSSES PREVENTED โ‚น14,679 /mo XGBoost pincode risk filtering
EST. MONTHLY REVENUE โ‚น629,100 /mo 900 orders @ โ‚น699 AOV

Generate a Manifest badge for your store

Customize and copy your verified operational badge or shipping manifest sticker.

MANIFEST SOLO STORE VERIFIED
โ— SYSTEM OPERATIONAL AUTONOMOUS V1

Technical principles

RULE01

Every number is labeled

If a value came from a live source, it's marked live. If a fallback estimate was used, that's marked too at the point of decision.

TRANSPARENT
RULE02

Outcome-gated learning

Pricing and risk models improve from real order outcomes automatically, gated so early noise can't swing the model.

BAYESIAN
RULE03

Quota-resilient fallbacks

Built to run inside free-tier API limits, with a ranked fallback chain so quota limits never stop the pipeline.

RESILIENT
Want to inspect or review Manifest's complete system architecture?