Sovereign by design
Customer-owned hardware today, with isolated cloud appliance options coming soon. The product is designed around controlled boundaries, not shared-cloud assumptions.
Investors
Investor conversations start with PairMind.
OmniqAI is building PairMind, an AI-native work-OS appliance for teams that need AI teammates, built-in work systems, and sovereignty by design.
We are not trying to add a thin AI layer to legacy work tools. We are building the workspace where humans and AI teammates operate as one team: chat, calls, docs, git, PM, calendar, office workflows, memory, governance, and 700+ tools built in.
The company site stays public-safe. Detailed traction, financials, valuation, and customer-specific pipeline are shared in direct investor conversations.
The thesis
AI will move deeper into daily work, but the teams with the highest trust requirements cannot give up control to use it.
Regulated and IP-sensitive teams need AI that can do real work, remember context, join collaboration, and operate under human judgment. They also need deployment control, auditability, and clear boundaries around what leaves the organization.
PairMind is OmniqAI's answer to that problem: an AI-native work-OS appliance where the experience, autonomy, governance, memory, and deployment model are designed together.
AI built in, not bolted on
Chat, calls, docs, git, PM, calendar, office workflows, CRM, HR, payroll, social-media workflows, and 700+ tools — with AI teammates native to every one, not bolted on after.
Governed autonomy
AI teammates act under digital-twin governance, with ALLOW / ASK / DENY controls and audit history.
Why now
The market is learning that AI adoption is not just a model problem. It is a work, trust, and deployment problem.
Most companies can try AI tools. Fewer can let AI touch sensitive meetings, code, deals, hiring, security, operations, and customer records. That gap is where PairMind is aimed.
The next useful AI system will not only answer questions. It will participate in work, remember context, act where it is allowed, stop where judgment is needed, and fit inside the buyer's operating boundary.
Work is collaborative
AI teammates need to live in the same work surfaces as people, including chat, calls, docs, code, PM, and handoff rituals.
Autonomy needs judgment
More agent power increases the need for explicit governance, not less.
Boundaries matter
Sensitive teams need a path to use advanced AI without sending everything into shared cloud systems.
What is public today
Enough to establish seriousness. Not enough to leak private diligence material.
Private beta
PairMind Appliance is in Private Beta with design-partner pilots as the intended sales motion.
Internal validation
OmniqAI has used PairMind internally for 9+ months across real planning, engineering, review, and operations workflows.
Product family
PairMind Appliance leads. PairMind iEval is launching soon. PairMind FrontDesk and Operator are in pilot.
Founder credibility
Udayendra Naidu G brings enterprise security and networking experience from RSA and Cisco, holds 3 patents, and builds the system hands-on.
DPIIT-recognized
OmniqAI is a DPIIT-recognized Indian deep-tech company building for global regulated and IP-sensitive teams.
What investors can request
The public page is intentionally light. The packet and conversation carry the diligence detail.
Product architecture
Appliance model, AI-native collaboration layer, governance, memory, and deployment roadmap.
Market and wedge
The target customer profile, design-partner motion, and how PairMind enters regulated teams.
Traction and roadmap
Current stage, validation, pilots, product milestones, and the next company-building priorities.
Founder and team
Founder background, dogfooding culture, hiring priorities, and operating model.
If the thesis fits, talk to us.
We are looking for aligned capital and strategic help, not generic attention.
The best investor conversations for OmniqAI are with people who understand enterprise trust, deployment friction, founder-led product depth, and the gap between AI demos and AI systems that actually run work.
