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Mindalike · Pre-Seed
The Collaborative
Operating System
for AI-Native Creation

AI generates code. Humans create products.
Mindalike makes it possible to do both — together.

Zerobase S4 · Seoul Top 97 AI Startups · F6S Pre-Seed · 2026

Mohd Murtuza Ali CEO  ·  Mirza Anwaarullah Baig CTO

www.mind-alike.com
01 — The Shift
Context
AI made building
faster. It made
coordination impossible.

Millions of builders can now generate code with AI — but the workflow infrastructure for teams building together with AI simply does not exist yet. That is the gap we are filling.

46%
of developers don't trust AI-generated code — spending 6–10+ hours per week manually fixing hallucinations and architectural failures
∞
Prompt loops — builders generate, hit failures, lose context, and restart from scratch. Alone. Every time.
0
Platforms built specifically for multiplayer AI-native software creation. Until now.
02 — The Problem
Four Coordination Failures
The bottleneck is no longer
code generation. It's coordination.
01
The Infinite Prompt Loop

Builders generate code → hit hallucinations → lose architecture → restart from scratch. This cycle repeats because AI has no persistent memory and no ability to coordinate recovery. Hours are lost. Progress stalls.

02
Solo AI Workflows Break at Scale

Every major AI tool — Cursor, Lovable, Replit — is optimized for single-player use. Modern product creation is collaborative. The infrastructure for teams to build together with AI does not exist.

03
Nontechnical Founders Hit a Wall

Founders can generate prototypes quickly. But they cannot reliably judge architecture, handle deployment, debug production failures, or assess security. They need human judgment inside the workflow — not outside it.

04
Collaboration Tools Aren't AI-Native

GitHub, VS Code Live Share, Slack — none were designed around AI agents, shared prompting, or persistent AI memory. They are retrofit solutions for a fundamentally different era of building.

03 — The Insight
"
AI can generate code.
It cannot judge.
The future problem is not output speed — it is:
Coordination Trust Architecture Shared context Ownership Product judgment Alignment Memory

The missing layer in AI software creation is human collaboration infrastructure — the platform that sits between people building with AI. That is the category we are building.

04 — How It Works
Product Flow
From isolated prompting to
collaborative product creation
1
Generate

Founder creates an AI-generated prototype inside Mindavibe. Every prompt and scaffold is visible to all collaborators in real time.

2
Collaborate

Team enters the shared AI-native workspace. Context is persistent. No one starts from scratch. Everyone builds on the same foundation.

3
Escalate

AI workflow fails — hallucinations, architecture blockers. A scoped expert joins the live session instantly, no full repo exposure needed.

4
Ship

Bottlenecks resolved. Context intact. Product launched faster than any single team member could have done alone.

Mindavibe IDE screenshot
Mindavibe IDE

Main multiplayer coding environment with shared context, active collaboration, and the build surface where the product actually happens.

Session invite screenshot
Session Invite
05 — The Product
Product Stack
Five layers. One platform.
⚡
Mindavibe IDE

Multiplayer AI-native coding environment. Shared prompts, synchronized context, live cursors, integrated video bubbles. Built for teams, not individuals.

KPI: Weekly collaborative sessions
🧠
Persistent Shared Context

Project memory, prompt history, and architectural decisions stored permanently across sessions and collaborators. AI loses context. Mindalike does not.

KPI: Context retention & repeat sessions
🔗
Human Escalation Layer

Instant expert access inside active workflows. Scoped, time-limited, and embedded — not a marketplace post. Not a Slack message. Inside the build.

KPI: Escalation resolution rate
🔒
Scoped Collaboration Access

Permission-controlled access modes — prompt-only, branch-specific, time-limited, sandbox — so teams collaborate safely without full repo exposure.

KPI: Enterprise adoption rate
🤝
AI-Native Team Formation

Intelligent matching of founders, engineers, designers, and specialists — based on active project context, skill gaps, and failure modes, not static profiles. Every Svatlana who joins creates demand for an Adnan. The network compounds.

KPI: Match-to-session conversion rate
06 — Why Now
Market Timing
Three shifts are converging.
The infrastructure doesn't exist.
1
AI generates software at scale

Millions of builders can prototype products in hours. The generation barrier is gone. The coordination barrier remains — and is growing.

2
Creation is becoming team-based

Individual AI tools are commoditizing. Competitive advantage now lives in how well teams coordinate around AI-generated work — not how fast any one person can prompt.

3
Existing tools weren't built for this

GitHub, Slack, and VS Code were designed before AI agents entered the workflow. They are foundational tools. They are not AI-native collaboration infrastructure.

"Mindalike is building the collaboration operating system for the AI-native era. The window for this is open. It will not stay open."

07 — Who We Build For
Two users. One platform.
A compounding network.
Svatlana
Svatlana
Non-Technical Founder
Goal
Move from AI prototype to a shipped, production-ready product
Pain
Trapped in infinite prompt loops with no trusted technical judgment to escape. Can generate. Cannot judge architecture or deployment.
✓ Matched with a technical collaborator. Builds inside Mindavibe with live human judgment in the loop. Escalates blockers instantly without giving full access.
Adnan
Adnan
Technical Builder
Goal
Find high-impact projects and aligned co-founders who share the same direction and build intent
Pain
Can't find collaborators matching build context, vision, or direction through cold profiles or job boards.
✓ Matched based on active project context, specific failure modes, and real-time build signal — not resumes or cold outreach.
Every Svatlana who joins creates demand for an Adnan. Every Adnan who ships attracts more Svatlanas. This is the network effect.
08 — Differentiation
Competitive Position
From single-player to multiplayer.
That is the entire shift.
Old World
Solo prompting in isolation
Fragmented, context lost between sessions
AI hallucination loops with no escape
Full repo sharing or no sharing at all
Async debugging across disconnected tools
Searching for collaborators on cold platforms
Mindalike
Multiplayer AI workflows
Persistent shared context across sessions
Human escalation system embedded in workflow
Scoped, permission-controlled collaboration
Real-time collaborative debugging
Intent-based matching from live build context
"Mindalike transforms AI software creation from single-player to multiplayer."
09 — Go-To-Market
Distribution
Start deep. Then grow wide.
Phase 1 — Seed the Right Community
50 deeply engaged startup teams. Not 10,000 random users.

We optimize for depth of engagement, not breadth of signups. The right early users generate the data, the word-of-mouth, and the retention curves that matter to investors.

YC applicants and active AI founders
Hackathon participants and winners
Indie hackers building with Cursor, Lovable, Replit
Technical co-founder seekers
Zerobase S4 and Seoul AI ecosystem
AI-native Discord servers and Slack communities
Phase 2 — Viral Growth Loops
Collaboration invites
Every active project naturally invites collaborators. The product distributes itself through every session started.
Shipped project showcases
Completed products built on Mindalike become social proof. Every launch is a distribution event.
Reputation visibility
Strong builders attract more collaboration requests. The network rewards participation with more participation.

Investor signal: organic growth · network effects · low CAC

10 — Traction
Early Validation
Early signals. Accelerating conviction.
150+
Waitlist users — zero paid acquisition
91K+
Community impressions — organic only
$8K
Cloud credits secured (Cloudflare + Google AI)
2×
Accelerator recognition (Zerobase S4 + F6S Top 97)
Accelerator Recognition
Zerobase S4 — Seoul · Active
F6S · Top 97 AI Startups Globally

North Star Metric

Weekly Collaborative Sessions — volume and week-over-week growth rate

Usage Growth — Demo Day Target
0 25 50 75 100 W1 W2 W3 W4 W5 W6 Demo Day target
11 — Business Model
Revenue Model
SaaS infrastructure first.
Platform economy second.
Free
$0
Limited matching sessions
Basic Mindavibe access
NetChat community
Pro
$20/mo
Unlimited matching
Full Mindavibe IDE
Persistent memory
Session replay
Most Popular
Team
$40/seat/mo
Everything in Pro
Scoped collaboration
Team context graph
Priority matching
Enterprise
Custom
SSO + advanced permissions
Dedicated infra + SLA
Custom integrations
Expert Escalation Economy — Phase 2

Optional paid specialist access inside live sessions. Platform fee on each collaboration. This is not a freelancer marketplace — it is an in-workflow, real-time human escalation system.

Why the Distinction Matters

The platform is primary. The escalation economy is secondary. It activates only once the collaboration network has sufficient density to make expert matching fast and reliable at scale.

12 — Defensibility
The Moat
Features become commodities.
Networks become platforms.
🌐
Shared Context Graph

Project memory, architectural decisions, and prompt history compound over time. The longer a team uses Mindalike, the harder it becomes to leave — their entire build history lives here. Switching costs grow with every session.

🔁
Collaboration Network Effects

More builders generate more collaboration data, which improves matching, which attracts more builders. The network compounds. No competitor can replicate this without first building the network.

🏗️
AI Workflow Infrastructure

Mindalike is embedded in the creation workflow itself — not alongside it. Teams don't use Mindalike as a tool. They build inside Mindalike. That is a fundamentally different switching cost.

📊
Collaboration Data Moat

Every session generates proprietary signals: who builds well together, what failure modes map to what expertise, what project types succeed. No competitor can buy or replicate this data — it requires the network to exist first.

"We are not building an AI coding tool. We are building collaborative intelligence infrastructure."
That distinction is worth billions in perception — and in long-term platform value.
13 — Roadmap
Execution Plan
Five phases to the default
operating system for AI-native teams
1
Now · Zerobase
Collaborative AI Workspace

Multiplayer Mindavibe IDE. Shared prompting. Persistent context. Real-time co-building. Live user feedback from Zerobase S4. Obsessive metric instrumentation begins here.

2
During Zerobase
Persistent AI Memory

Full context retention layer. Session replay. Cross-project memory. Collaboration history. Infrastructure runway funding secured.

3
Demo Day → GA
Human Escalation Layer

Scoped expert access inside live sessions. Escalation routing. General Availability public launch. Viral invite loops activated.

4
Post-GA
Team Formation Network

Full matching graph. Reputation scoring. Trust infrastructure. Builder marketplace of intent — not labor. Enterprise and startup team pricing begins.

5
Scale
Collaborative Intelligence Platform

The default operating system for AI-native product creation. Every AI-native startup team runs on Mindalike.

Product roadmap screenshot
Product Roadmap

Roadmap board showing phases and completion status for execution proof.

14 — Vision
✦ Collaborative Intelligence Infrastructure
The future is not
AI replacing humans.
It's humans orchestrating
AI systems — together.

The companies that define this decade will be the ones that owned the workflow between people and AI systems — not just the AI systems themselves. Slack won team communication. Figma won team design. GitHub won team version control. Mindalike wins team AI creation.

15 — The Ask
Pre-Seed Round
Let's build the
human-in-the-loop
era together.

We are raising pre-seed capital to prove engagement velocity, build the collaboration network, and become the default layer for AI-native software creation.

Mohd Murtuza Ali — CEO · mdmurtuzaali777@gmail.com
Mirza Anwaarullah Baig — CTO · manwaarullahb@gmail.com
Team — team@mind-alike.com
www.mind-alike.com
Use of Funds
⚙️
Real-time collaborative infrastructure and low-latency synchronization systems
🧠
AI memory, context persistence, and session replay architecture
🛠️
Product engineering — Mindavibe IDE and AI-native matching layer
📡
Compute and AI infrastructure to extend Cloudflare and Google AI credits
🚀
Early community growth and GTM execution targeting 50 engaged startup teams
Mission: Become the default collaboration layer for AI-native software creation. The window for this category is open. The infrastructure does not yet exist. That is what we are building.