On-device voice-to-text writing console

For

Writers and knowledge workers who dictate into desktop apps on their own computer

Solves

Dictation tools split speech-to-text, cleanup, research and task actions across several subscriptions, and most send audio to a cloud service.

Delivers

Reviewed, source-linked dictated text and voice-triggered actions

Built in

about 4 weeks of creation time, MVP in 5 days

Investment

$13,500 for the MVP, $46,000 for the full product

Run it

Inside your business, or as part of your offer to clients

Reduce the number of rented dictation tools while keeping dictated text, style data and voice commands on the writer's own machine.

1. Transcribe speech on-device with a local model.
2. Dictate into any app or website with a text field.
3. Start and stop dictation with a keyboard shortcut.
4. Add grammar and punctuation during transcription.
5. Produce text with low latency as the writer speaks.
6. Keep the interface minimal and out of the way.
7. Create notes and tasks from voice commands.
8. Maintain custom dictionaries for names, code and special terms.
9. Return cited web answers inside the workflow.
10. Accept a bring-your-own API key for a chosen cloud provider.
11. Switch between person-facing and AI-facing output modes.
12. Restore the clipboard after inserting dictated text.
13. Keep storage and memory use small.
14. Detect the active app and send text with the right command.
15. Apply app-specific tone and formatting profiles.
16. Learn the writer's style from local samples.
17. Perform voice-triggered actions such as creating tickets or editing calendar entries.
18. Capture quiet speech for use in shared spaces.
19. Compare the reviewed result with the recorded baseline and value assumptions.
20. Capture corrections and named-owner approval before consequential use.
21. Export a versioned reviewed dictation record with source references and unresolved questions.

Everything these tools do, in one app

• On-device speech-to-text Converts your speech into text using models that run locally on your computer.Found in AI dication by Snaply, Voicetypr, VibeSonic and 4 more
• System-wide dictation Lets you dictate into any app or website where you can type.Found in AI dication by Snaply, Voicetypr, VibeSonic and 3 more
• Hotkey activation Starts and stops dictation with a keyboard shortcut.Found in AI dication by Snaply, Yap
• Automatic grammar and punctuation Adds or adjusts grammar and punctuation while transcribing.Found in AI dication by Snaply
• Low-latency transcription Produces text with minimal delay so it appears almost as you speak.Found in AI dication by Snaply, Voicetypr, Clippy, but on Steroids
• Minimal interface Keeps the app visually simple and out of the way while you work.Found in Voicetypr, Stet
• Voice-driven notes and tasks Creates notes and tasks using voice commands.Found in VibeSonic
• Custom dictionaries Lets you add names, code, or special terms to improve recognition.Found in VibeSonic
• Web research assistant Returns cited answers from the web without leaving your workflow.Found in VibeSonic
• Bring-your-own API key Lets you plug in your own API key to use a cloud provider you choose.Found in VibeSonic, Stet
• Two-mode output Adjusts how much the text is refined depending on whether it is for a person or an AI.Found in Stet
• Clipboard preservation Keeps your copied content intact by restoring the clipboard after inserting dictated text.Found in Yap
• Small resource footprint Uses very little storage and memory so it runs lightly on your machine.Found in Yap
• App-aware sending Detects the active app and sends the text with the right command automatically.Found in GHOSTYPE
• App-specific tone profiles Switches tone and formatting based on which app you are using.Found in GHOSTYPE
• Local style learning Learns your writing style from your computer so output matches your voice.Found in GHOSTYPE
• Voice-triggered actions Performs tasks like creating tickets or editing calendar entries from voice commands.Found in Clippy, but on Steroids
• Whisper-friendly microphone Captures quiet speech so you can dictate in shared spaces.Found in OASIS 1 Ring

What goes in, what comes out

The workflow

1. In
   Start with

   Microphone audio, custom terms, app context and the writer's own style samples

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect microphone audio

4. 3

   Custom terms

5. 4

   App context and the writer's own style samples

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Reviewed, source-linked dictated text and voice-triggered actions

AI does the heavy lifting, people stay in charge

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Local speech models run on the writer's machine; cloud providers are optional and only through the writer's own API key. Final wording, factual accuracy and any external action remain the writer's. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Dictation overlay, Style and dictionary settings, Review and history console. Use a small always-available overlay for recording state, a settings panel for hotkeys, dictionaries, tone profiles and API keys, and a console listing past dictations with source audio, inserted text, corrections and linked actions. Let users compare raw and refined text side by side. Display draft, corrected and approved states. Provide a per-app profile view with the active tone and send command. Make the task-specific outcome reviewed, source-linked dictated text and voice-triggered actions visible beside its evidence, review state and value baseline.

Accounts and administration

Device ownership, model versions, dictionary entries, tone profiles, API key records, action permissions, correction history and a rights record for supplied material. Add organization access boundaries, named reviewers, usage caps, data retention controls, export logs and explicit approval for external actions.

Integrations and data access

Writer-owned documents, authorized meeting audio and permitted research sources. Desktop text fields, clipboard, calendar and ticket systems. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

1. 1

   Scoping call

   Day 1

   Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

2. 2

   MVP

   5 days

   One buyer segment, one recurring use case; first modules: transcribe speech on-device with a local model; dictate into any app or website with a text field. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   6 days

   Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

4. 4

   Full product

   10 days

   Self-serve onboarding, billing, monitoring and the wider integration set.

5. 5

   Run and improve

   Monthly

   We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

1. Pick the riskiest assumption. Here: will writers and knowledge workers who dictate into desktop apps on their own computer use it to solve "dictation tools split speech-to-text, cleanup, research and task actions across several subscriptions, and most send audio to a cloud service"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. Agree quality and outcome thresholds before the pilot using this measure: Accepted dictated words per hour and correction rate after insertion.
4. Measure, then decide. Track accepted dictated words per hour and correction rate after insertion; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Pilot scope: One desktop operating system and one local speech model; final wording and external actions remain the writer's. Implement one approved input format, a bounded representative case set and the first two task modules: transcribe speech on-device with a local model; dictate into any app or website with a text field. Support the third module with operator review: add grammar and punctuation during transcription. Include source references, corrections, basic device access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.

After the MVP. Once paid pilots prove usefulness, automate repeatable reviewed steps and add one verified source integration. Expand supported inputs and case volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around reviewed, source-linked dictated text and voice-triggered actions. Retain the explicit scope boundary: One desktop operating system and one local speech model; final wording and external actions remain the writer's.

What the build depends on. Microphone capture, local model packaging, asynchronous transcription jobs, editable version history, reviewer access and tested export formats. High-fidelity production requires specialist writing QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One desktop operating system and one local speech model; final wording and external actions remain the writer's.

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

Your brand, or this one

Run it under your own brand, or start from this concept style.

Selling it to your own clients: the go-to-market playbook

Pricing to test

Test a USD 300-1,500 fixed pilot for one defined device and workflow package. Offer a monthly production allowance after repeat demand. Quote complex integrations or specialist review separately. These are test prices, not market benchmarks. Package the initial sale as one bounded reviewed, source-linked dictated text and voice-triggered actions. Recurring fees must specify volume, review depth and integration support. For exchanges, test a disclosed coordination or successful-service fee rather than holding customer funds. Reprice only after measuring real delivery labor; platform-build cost is separate from a commercial pilot fee.

Message to test

Reduce the number of rented dictation tools while keeping dictated text, style data and voice commands on the writer's own machine. Demonstrate a concrete reviewed, source-linked dictated text and voice-triggered actions using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Writers and knowledge workers who dictate into desktop apps on their own computer professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample reviewed, source-linked dictated text and voice-triggered actions from a small authorized input set, with a transparent calculation of accepted dictated words per hour and correction rate after insertion and no promised savings.

The first 30 days

1. Week 1: interview five writers and knowledge workers who dictate into desktop apps on their own computer and inspect a recent example of dictation tools split speech-to-text, cleanup, research and task actions across several subscriptions, and most send audio to a cloud service.
2. Week 2: prepare a consented or synthetic demonstration of the three task modules.
3. Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
4. Week 4: measure accepted dictated words per hour and correction rate after insertion, reviewer effort and repeat-purchase interest. This is a demand-validation plan, not a thirty-day full-product delivery promise.

Paid pilot

Agree quality and outcome thresholds before the pilot using this measure: Accepted dictated words per hour and correction rate after insertion. Continue only if the buyer accepts the actual output, the intended job outcome improves without unacceptable errors, and measured delivery cost fits willingness to pay. Revise or stop if access is unavailable, qualified review cannot be provided, or apparent savings disappear after corrections and support. Use held-out cases when comparing model quality; use a properly reviewed comparison design before making causal claims. Record missing cases and negative results alongside successful outputs.

Success metrics

Accepted dictated words per hour and correction rate after insertion; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs reviewed, source-linked dictated text and voice-triggered actions. Retain permissioned settings and reviewed examples, report realized value honestly, and sell increased volume or adjacent approved workflows only after contribution margin and quality remain acceptable.

Why clients would pick it

A reusable library of approved dictionaries, tone profiles and review examples, together with reliable delivery for a narrow writing niche. Build a permissioned library of representative task cases, writer corrections and verified operating constraints for writers and knowledge workers who dictate into desktop apps on their own computer. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

AI dication by Snaply, Voicetypr, VibeSonic, Stet, Yap, GHOSTYPE, OASIS 1 Ring and Clippy, but on Steroids, plus operating-system dictation and manual typing. Compare this product with the buyer's present method on accepted dictated words per hour and correction rate after insertion. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Local model packaging, cloud API calls made with the writer's key, storage, reviewer hours, writer revision rounds and licensed source assets. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of reviewed, source-linked dictated text and voice-triggered actions. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve writer voice, source attribution, quotation accuracy and usage permissions. Writers approve substantive changes and external action scope. One desktop operating system and one local speech model; final wording and external actions remain the writer's. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.