Adarsh S Mcold start
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Sigil

Handshake deals into binding micro-contracts

An AI-native mobile app that turns a spoken agreement into a binding digital micro-contract, with the language model running on the device so the conversation never leaves the phone.

Where
Sigil — founder
When
2026 — present
Role
Founder — product, architecture, roadmap
Stack
On-device SLMs · Speech processing · Mobile · Privacy-first architecture · Subscription product
72.9MTarget marketindependent workers in the freelance economy
0Cloud round-tripsvoice never leaves the device

Problem

Most freelance work still starts as a handshake — a voice note, a call, a verbal yes. None of it is enforceable, and the tooling that would make it enforceable is slow, expensive and built for enterprise legal teams rather than for one person who needs cover before starting a job tomorrow.

Constraints

  • 01Voice data cannot leave the device — this is a privacy product or it is nothing
  • 02Zero-latency processing, because dictating a deal should feel like talking
  • 03A consumer product with a subscription, deliberately not a custom agency service
  • 04Bootstrapped: every architectural choice has to be affordable to run at zero revenue

Architecture

CAPTUREUNDERSTANDFORMALISEBINDSTOREVoice capturespoken agreementOn-device speechno uploadOn-device SLMzero-latency inferenceTerm extractionparties, scope, price, dateContract synthesismicro-contractHuman reviewboth parties confirmDigital signaturebindingLocal-first storeuser owns the data
fig.01The model runs on-device. That single decision determines the privacy story, the latency story and the unit economics simultaneously.

Key decisions & trade-offs

  • A small model on the device, not a large one in the cloud

    A cloud LLM would be more capable per token. But it would also mean uploading a recording of a private negotiation, adding a network round-trip to something that should feel instant, and paying per inference for a product with no revenue yet. An SLM on-device answers all three at once.

    Trade-offYou give up raw capability and you inherit the device's memory and thermal limits. The scope is narrow enough — extract terms from a short spoken agreement — that a small model can carry it.

  • A consumer product, not an agency

    The fastest revenue for a solo founder with these skills is bespoke client work. That is also a business that cannot compound. Sigil is deliberately a subscription product so the work done this month still earns next month.

    Trade-offMuch slower to first revenue, and it means saying no to consulting that would pay immediately. It is the difference between a job and a company.

  • Human confirmation before anything binds

    The model drafts; it never commits. Both parties see the extracted terms in plain language and confirm before a contract exists. An extraction error should cost a correction, not a legal dispute.

    Trade-offIt adds a step to a flow whose entire pitch is speed. Given the output is legally binding, that step is not optional.

Results

72.9MAddressable usersindependent workers in the freelance economy
0Cloud round-tripson-device SLM inference