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ForthWrite is an AI email writing assistant for Gmail and Outlook that learns your writing style from your real sent mail. The more you use it, the more it sounds like you. Get smart drafts in seconds, auto-draft replies before you open your inbox, and maintain your personal voice at scale. Free to start, no credit card required. Works inside Gmail and Outlook on the web.
How it works
ForthWrite captures your tone, sentence rhythm, and sign-offs from your actual sent emails, then uses that profile to generate drafts that match how you write, not a generic AI voice. Every draft you edit or send improves the model over time.
Key features
Who uses it
Professionals who send high volumes of relationship-critical email: lawyers, financial advisors, recruiters, account executives, founders, and anyone who wants their inbox handled without sounding like a chatbot wrote it.
Pricing
Free tier includes 10 drafts per week with no credit card required. Paid plans start at $12/month and include unlimited drafts, custom persona prompts, and auto-draft.
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ForthWrite's answer:
Next.js, React, Supabase, Anthropic Claude, OpenAI, Stripe, Vercel, Chrome Extensions API
ForthWrite's answer:
ForthWrite learns your writing style from your actual sent mail, not a generic prompt. Every draft sounds like you wrote it because it was trained on how you actually write. It also auto-drafts replies before you open your inbox, so your email is partially handled before your day starts.
ForthWrite's answer:
Most AI email tools give you a blank box and a "write for me" button. ForthWrite builds a voice profile from your sent history and gets more accurate with every draft you edit or send. Unlike ChatGPT or Gemini, it works natively inside Gmail and Outlook with no copy-paste. Unlike Lavender, it writes the draft, not just scores it.
ForthWrite's answer:
Professionals who send high volumes of relationship-critical email and cannot afford to sound generic: lawyers, financial advisors, recruiters, account executives, consultants, and founders managing their own inbox.
ForthWrite's answer:
Built out of frustration with AI writing tools that produce text that sounds nothing like the person sending it, and as a way to handle large amounts of daily email. The core insight was that your sent mail is the best training data you already have, and no tool was using it.
I built ForthWrite because I kept sending emails that sounded like they came from the same generic AI as everyone else. After launching it, I still use it for my own inbox every day, which is about the most honest endorsement I can give.
The Chrome extension lives inside Gmail and Outlook on the web. Open a thread, hit Alt+Shift+D, and a draft comes back in your voice, not a template. The free tier is real: 10 drafts per week, no API key, no credit card. Voice matching is included on free, because that is the point.
What keeps it useful compared to Gemini or a chat tab: it learns from what you actually send. Every edit you make before hitting send becomes a signal. Over time the drafts drift closer to how you really write, and the dashboard shows the improvement curve so you can see it happening.
The web compose surface lets you draft from forthwrite.ai without installing anything, useful for people who want to try before committing to the extension.
Standard adds recipient-aware and intent-aware drafting plus AI coaching. Pro adds auto-draft (replies waiting when you open Gmail), batch replies, and Prompt Lab for version-controlling your prompts. Teams adds a shared persona and seat-level analytics.
ForthWrite is not for everyone. If you just need quick replies and tone does not matter, Gemini is free and already in your inbox. ForthWrite is for people where tone does matter: client communication, relationship-driven threads, external correspondence where sounding off costs something real.
Disclosure: I am the founder and use it daily. Happy to answer questions in the comments.
Based on our record, Prodigy seems to be more popular. It has been mentiond 25 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
This is really cool. The annotation-to-testing-to-annotation-etc. Feedback loop makes a ton of sense, and I'd encourage others who may be confused on this post to look at the Automotus case study https://encord.com/customers/automotus-customer-story/ for the annotation side, but my understanding is the relationship between model outputs and annotation steering is out of scope for that project - do you know of... - Source: Hacker News / over 2 years ago
Spacy [0] is a state-of-art / easy-to-use NLP library from the pre-LLM era. This post is the Spacy founder's thoughts on how to integrate LLMs with the kind of problems that "traditional" NLP is used for right now. It's an advertisement for Prodigy [1], their paid tool for using LLMs to assist data labeling. That said, I think I largely agree with the premise, and it's worth reading the entire post. The steps... - Source: Hacker News / almost 3 years ago
Prodigy AI - Offers software engineers career coaching, skill assessment, and job matching. Visit Prodigy AI. - Source: dev.to / almost 3 years ago
I essentially want to use a Combo of OCR + NER to attempt to identify this, but I'm not sure NER is well suited for this, as it is not natural language, so there is little context to go off of. I was thinking of perhaps using Prodigy, a data annotation tool, to annotate Candidate Names, Races, etc, and perhaps it will be able to learn off of image data alone wheat these fields tend to look like. Source: over 3 years ago
I come from a similar application area, where I try to tag (annotation/label) a taxonomy of products iteratively. You are trying something slightly different, AFAIU, labeling a flat set of songs, each song with a set of tags from ontology (directed graph)From an application point of view, this is what taxonomists often do, when migrating products from one catalog to another: mapping one taxonomy to another. There... Source: over 3 years ago
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