Customer Experience,
Reimagined

Hsieh
HSIEH
Unlock the Power of AI to
Capture, Understand, and Act on
Every Customer Problem Seamlessly

Manual Process

It takes seconds to get feedback, and weeks to process it. 80% of its value dies in the queue.

Unscalable Infrastructure

When things break, you have 10 times the data, and zero ability to act on it.

Revenue Loss

Customers don't care about your process. The longer they wait, the faster they leave.

The Problem

Companies have a lot of data and insights, but still customer problems take time to resolve.

The Solution

Hsieh uses AI agents to eliminate manual work and optimise workflows. We turn delayed data into action and frustrated customers into loyal ones.

Agent Call
Email
Social/Web
IF: Support Request
IF: Billing Issue
HIGH PRIORITY ANOMALY DETECTED
Alert Team
Issue Refund
Close Ticket

What Hsieh delivers.

  • Plugs into every customer channel. You never miss a complaint.
  • Agents collect feedback on autopilot. Zero manual busywork.
  • Analyzes the actual problem instantly. Stop guessing, start solving.
  • Automatically prioritizes critical issues. Your team always knows what to fix first.
  • Spots sudden ticket spikes instantly. Kill the crisis before it spreads.
Dashboard Screenshot

What Sets Hsieh Apart?

Advanced NLP Technology

Understands context
and intent.

Privacy-First Approach

End-to-end encryption
for data security.

Engineered for action.

Instantly performs action
and deliver insights.

With advanced NLP, it understands context. A privacy-
first approach keeps your data safe. Real-time
efficiency delivers instant action and insights.

Capabilities

Autonomous Action.

More than just analytics. A system that executes on its own.

End-to-End Autonomy

Directly resolves issues and completes workflows without human oversight.

Self-Healing Logic

Dynamically learns from edge cases to adapt its own operational parameters.

Executable Output

Interacts directly with APIs to trigger refunds, follow-ups, and CRM updates.

Case Study

Bank Alfalah.

Transforming a legacy institution into a digital powerhouse overnight.

Before
PKR 109
Cost per Feedback
10
Team Size
10-20%
Efficiency
Analyzed
800k
Feedbacks
After
PKR 11
Cost per Feedback
1
Team Size
80%+
Efficiency

The Roadmap.

A clear path to dominance.

Q1 2026

Core Launch

Initial Client Onboarding

Q2 2026

Alfalah Integration

Enterprise Dashboard

Q3 2026

Global Expansion

Multi-language Support

Q4 2026

AI Optimization

Predictive Analytics

The Feedback Index.

Comparing traditional methods against AI-powered execution.

Manual Systems

Slow, leaky, and reactive.

All Feedback Collected40-50%
Analyzed10%
Drives Action5%

Feedback Index

5

Hsieh AI

Autonomous, instant, and actionable.

Feedback Captured80%
Analyzed~100%
Actionable Items~70%

Feedback Index

70

The right team for the job.

A small team obsessed with solving big problems.

Hassan Askari

CEO / Founder

  • 2× Founder
  • Led Groomify acquisition
  • CS Graduate — AI & Design Language

Kumail Bukhari

CTO / Founder

  • 1× Founder
  • Founded Asaniyan (Healthtech)
  • Expert in AI & Machine Learning
  • Built & trained AI models from ground up

Talib Rizvi

Growth Partner

  • 20 years of Banking experience
  • Ex Chief Gov. Relations, Jazz
  • Advisor to CEO, Jazz
  • Ex Exec, Bank Alfalah

The Strategy.

A blueprint for hyper-growth.

1
Capture

Dominate the initial enterprise niche seamlessly.

2
Expand

Leverage case studies like Alfalah for inbound growth.

3
Scale

Automate onboarding to handle mass global adoption.

An expanding frontier.

The digital economy is accelerating.

TAM

$25B
CAGR 18–20%

SAM

$8B

SOM

$300M

The Numbers.

Sustainable growth, predictable economics.

The Ask
$1.5M

Seed Round

18 months runway to scale GTM.

Target
$5M+

Year 3 ARR

Driven by enterprise expansion.

Projected Breakdown (Year 1)

Projected Revenue $1,200,000
COGS $180,000
Gross Margin (85%) $1,020,000

Operating Expenses

R&D / Engineering (40%) $600,000
Sales & Marketing (35%) $525,000
General & Admin (25%) $375,000
Net Burn ($480,000)