$3.4M Seed Round Open

Invest in the Next Generation of Privacy-First Edge AI

PairHint is an on-device, real-time AI copilot for high-stakes conversations. It listens, sees your screen and remembers your documents, with no cloud round trip and nothing leaving the machine. Live today on macOS, Apple Silicon and Intel.

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$3.4M

Seed round

< 5 months

to go-to-market once funded

1,000

paying users by end of year 1

400K

paying users 6-year projection

Why Invest in PairHint?

Why PairHint is different: Capturing audio and screen and answering in real time is far harder than it looks. That difficulty is the moat.

100% On-Device Moat

Zero cloud hosting costs, zero data tracking. Runs local GGUF models directly on user GPUs/CPUs via optimized C++ bindings.

No cloud round trip

Light Unit Economics

Subscription plus session-hour top-ups, with local inference so each new user adds little marginal cost. Planning assumption: 85% of gross revenue kept after fees, refunds, hosting and support.

85% net revenue

Multi-Vertical Adaptations

Expanding beyond meetings into Medical clinical notes, Legal depositions, Enterprise Sales, and Field Engineering.

36.5M developer TAM

Rapid Revenue Scalability

Planning case at a $20/month blended price: 20K paying users and $3.0M gross revenue in year 3, 200K users and $33.0M in year 5. Teams, enterprise and platform revenue are not included.

$33M Year 5 (gross)

Multi-Engine Orchestration

Choose between speech engines (AUTO multi-STT) and AI engines (LLM1 Best, LLM2 Good) to balance accuracy and speed for each question, and freeze an answer on screen when needed.

Switch engines live

Capital-Efficient Growth

No server GPU fleet to fund. The seed goes to product and AI (40%), go-to-market (35%) and trust and scale (25%).

$3.4M seed

More than an LLM window: a real-time context pipeline

The reusable asset is the pipeline itself: capture, context, inference and presentation, all tuned for latency.

1 · Listen

Dual-channel audio

Microphone and meeting audio on two channels, with noise filtering and live question detection.

2 · See

Screen + OCR

Reads problem statements, diagrams and documents straight from the shared screen.

3 · Remember

Persistent context

Uploaded documents, role and presentation context, and the conversation so far.

4 · Assist

Structured answers

A one-line answer first, then key points, code, complexity and follow-ups, streamed while the conversation continues.

Founder pitch

A multi-billion-dollar opportunity across live-conversation roles

Designed for live conversations across professional roles in sales, consulting, law, healthcare, technical support, and engineering.

$12.5B

TAM

52M jobs in six live-conversation roles across 4 global regions.

$6.0B

SAM

~25M jobs in sales, consulting, law, and technical support.

$72M

SOM

Year-6 revenue target (400K paying users): 1.2% of SAM, 0.6% of TAM.

Why PairHint is different

Capturing audio and screen and answering in real time is far harder than it looks. That difficulty is the moat.

Chat AIMeeting assistantsPairHint
Live audio awarenessUser-providedMeeting-focusedDual-channel capture
Screen contextManual uploadVariesScreen analysis + OCR
Personal documentsFiles / promptsLimitedPersistent session context
Technical outputGeneralGeneralCode + explanations
Privacy modelCloudCloudOn-device
InterfaceSeparate windowMeeting UIFloating overlay

📈 Revenue & Subscriber Growth Trajectory

Planning case: 400,000 paying users and $72M gross revenue by year 6, about 1.1% of professional developers.

Financial Model Assumptions
  • Blended Price: $20/mo ARPU (Subscription + Top-ups)
  • Net Revenue: 85% of gross revenue
  • Launch Window: Within 5 months (Year 1 is partial)
  • Scope: Pure B2C (Teams & Enterprise expansion upside excluded)
PairHint Revenue Projection Graphic
Six-Year Cumulative Revenue $120.2M Gross • $102.2M Net

$3.4M seed allocation and key growth milestones

40%

Product & AI · $1.36M

  • Latency & inference optimization
  • Multi-engine FFI bindings
  • Hardware acceleration (Metal/CUDA)
  • Quality & accuracy benchmarks
35%

Go-to-Market · $1.19M

  • Customer acquisition channels
  • Developer & executive outreach
  • Enterprise B2B pilots
  • Funnel conversion optimization
25%

Trust & Scale · $0.85M

  • On-device encryption architecture
  • Enterprise readiness & compliance
  • Multi-tenant seat management
  • Platform infrastructure

Key Seed Milestones

  • Multi-vertical rollout (Legal/Medical/Sales)
  • $3.0M Gross ARR target milestone
  • Enterprise seat distribution scaling
  • On-device privacy leadership
PAIRHINT + GENTA

GENTA: sees, hears, reads, remembers, thinks and creates

GENTA is our research project for a compact, general-purpose AI model. It brings together images, speech and text, multiple levels of memory, reasoning and content generation in one architecture. PairHint provides a concrete first application; GENTA’s potential goes much further.

PairHint is the first application. GENTA can go further.

PairHint today

Several AI models work together to listen, see the screen, remember context and answer in real time. Coordinating them adds integration work, processing overhead and delays.

GENTA: the development goal

Bring perception, memory, reasoning and response generation together in one compact model. The aim is faster responses, lower running costs and easier deployment on local devices.

Connects what it sees, hears and reads

Combines images, speech and text so the model can use information from them together.

Learns how the world changes

JEPA, a predictive learning approach, trains the model to anticipate what comes next from the information it observes.

Supports multiple memory levels

Working and short-term context, plus long-term and very long-term memory, help the model use earlier information.

Reasons and creates

Symbolic reasoning uses explicit mathematical operations to improve reliability. Generation capabilities span text, speech, images, 3D objects and video.

One architecture, many tasks

An initial 65 training tasks develop different skills within one model, providing a foundation for broader applications.

Learns in parallel

Multiple synchronized instances train together and share learning updates, designed to accelerate learning across multiple processors.

A reusable AI foundation beyond PairHint

The same architecture could support education, professional assistants and creative tools. Improvements to the shared model could benefit multiple products, opening opportunities beyond a single application.

PairHint is the near-term business. GENTA is the longer-term research opportunity; efficiency and full product integration remain development goals.

Explore the GENTA architectureGENTA architecture showing perception, memory, prediction, reasoning and generation

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