Connect
Parbat
Pricing infrastructure for modern commerce.
Parbat helps commerce brands ship profitable price changes with Evidence Before Exposure
We do not ask teams to trust a recommendation blindly.
Parbat discovers opportunities, scores likely upside, validates before exposure, and ships only what is safe and worth doing.
Pricing is one of the highest-leverage decisions in commerce — and one of the least operationalized
A commerce brand sees the same pattern every week:
01
Underpriced bestsellers
Margin leaks because teams are afraid to touch winners.
02
Over-discounted inventory
Brands cut price to move stock even when it destroys gross profit.
03
Debated Price Increase
Teams suspect a move is right, but lack the confidence to ship it.
04
Inefficient Process
Pricing becomes slow, inconsistent, and hard to scale across the catalog.
The problem is not one catastrophic pricing mistake. It is hundreds of small, unmade or mis-made decisions compounding across the catalog, week after week.
Current tools show signals. They do not produce safe pricing decisions.
Current solutions break at the exact point where a brand needs help: decision-making and safe execution.
Dashboards
Show what happened.
Do not tell the team what to do next
Repricers
Automate changes.
Often without enough business context, trust, or governance.
Experimentation Tools
Learn on live traffic.
After customers are already exposed.
Manual Workflows
Depend on judgment.
Slow, inconsistent, and hard to run across a catalog.
The missing layer is safe, governed pricing decision-making.
Parbat turns pricing into an Evidence-Before-Exposure system
Discover
Normalize pricing signals across traffic, conversion, sales, inventory, margin, discounting and price history.
Score
Identify candidate price moves most likely to improve incremental gross profit.
Simulate
Model expected demand response and projected economic impact before launch.
Verify
Check storefront execution, policy constraints, and business guardrails, then generate an Evidence Pack.
Ship
Launch only the price changes that are verified, economically attractive, and worth doing.
Parbat does not stop at insight. It helps teams ship pricing decisions with evidence and control.
A pricing workspace built reviewing and shipping price changes
Parbat provides an intuitive interface for managing pricing with precision.
Daily Briefing
Ranked daily list of highest-impact price opportunities, backed by Evidence
On-demand Recommendation
Decision-ready recommendation for a product, variant set, or merchandising group.
Validate Move
Baseline-versus-proposed comparison that shows projected impact, verified safety, and a clear verdict.
Every workflow produces the same core artifact: an Evidence Pack, and a decision-ready path to ship.
Simulation helps Parbat evaluate pricing moves before exposure
  • Score economically attractive candidate moves.
  • Simulate projected impact.
  • Verify whether the move is safe to ship.
The point is not to ask teams to trust a black box. It is to make pricing trustworthy enough to act on with confidence
Why now
The market is ready for pricing to become a system, not a spreadsheet exercise.
Margin pressure is forcing discipline
Brands can no longer rely on blanket discounting and reactive promotions to protect growth.
The technical stack is finally ready
Shopify-native data, modern workflows, and production-grade infrastructure now make continuous pricing systems possible.
AI is accelerating, but trust is the bottleneck
The missing layer is not another recommendation engine. It is a controlled system that validates and governs changes before exposure.
Brands want workflow-native tooling
Teams want software that fits how pricing decisions are actually made: review, validate, approve, ship, and learn.
Parbat arrives at the moment when pricing can finally become operational software — not just analysis.
Pilot wedge: prove one profitable pricing win in 3 weeks
Start with Shopify DTC brands that:
have 50–300 active products
manage pricing manually or semi-manually
feel margin pressure
have enough traffic for product-level decisions
21-Day Pilot Plan Timeline
Week 1
Connect store, ingest catalog and pricing context, define guardrails
Week 2
Run Daily Briefing and validate a small set of opportunities
Weeks 3
Ship 1-3 safe decisions and measure early outcome
Success Criteria
One validated pricing win
One repeatable workflow inside the team
One case-study-quality result
We are not asking brands to change their whole pricing stack on day one. We are proving one controlled win first.
Why Parbat wins
Dashboards
Show signals
Do not produce decisions
Repricers
Automate price changes
Often without enough business context or governance
Experimentation Tools
Learn after exposure
Not before it
Parbat
→ Discover
→ Score
→ Simulate
→ Verify
→ Ship
Others help teams analyze, automate or test. Parbat helps teams decide what is safe and worth shipping.
Beachhead: Shopify brands with enough catalog complexity to need a system
We are starting with US Shopify DTC brands with 50–300 active products.
Catalog complexity makes pricing pain real.
Sufficient traffic enables product-level decisions.
Lean teams lead to manual pricing.
High willingness for software that boosts margin without added headcount.
The initial sell is not autonomous pricing. It is a safer, more credible path to better pricing decisions.
We land with one narrow promise: help the team ship a small number of profitable, safe price changes quickly.
Land pilots → prove lift → scale through Shopify-native distribution
Our go-to-market strategy focuses on a disciplined, three-stage approach to acquire and grow customer relationships.
Land
Founder-led outreach to founders, heads of eCommerce, and brands in the beachhead segment.
Prove
Generate measurable pricing wins and turn them into strong case studies with quantified impact.
Scale
Grow through a robust Shopify-native presence, partner agencies, and customer proof points.
Start with decision support. Expand into governance, controlled execution, and closed-loop learning.
A small number of good decisions can justify the software
Business Model
  • Subscription software
  • Usage-aware packaging
  • Catalog / opportunity tiering
  • Premium controls for larger brands
  • Optional later: Performance-linked pricing for select accounts
Illustrative ROI example
For a brand with:
  • 150 active products
  • Top 30 products driving most demand
  • Average gross profit per order = $24
If Parbat helps the team ship just 2 profitable pricing moves per month:
  • Move 1: +$1,800 monthly gross profit
  • Move 2: +$1,200 monthly gross profit
  • Total monthly Gross Profit lift: $3,000
  • Monthly software cost: $1,000
Example output: illustrative
A small number of shipped, profitable pricing moves can justify the subscription. Incremental Gross Profit is the core value lens.
We are selling profit improvement, confidence, faster decision cycles, and governance — not just analytics.
Team
Farrukh Zaman
Co-Founder & CTO
Technology leader with 25+ years of experience building platforms, teams, and decision systems across enterprise software and AI-native products.
At Salesforce and Cisco, I led large-scale initiatives across cloud migration, DevOps, security, release systems, and operating infrastructure.
I'm building Parbat around the belief that pricing should be an operating system, not a spreadsheet exercise.
Ask
We are raising $250K SAFE (pre-seed) to complete the first proof loop: paid pilots, measured wins, and repeatable distribution.
Use of funds
  • convert pilot brands into paid customers
  • produce strong case-study-quality results
  • harden the production pricing workflow
  • validate Shopify-native acquisition
  • tighten the loop between recommendation and realized outcome
We are raising against a specific milestone: turn Evidence Before Exposure into a repeatable, paid wedge in Shopify commerce.