Software Alternatives & Startups

mlsql VS speaking.app

Compare mlsql VS speaking.app and see what are their differences

mlsql

Infer SQL queries from plain-text questions and table headers.

Rating
0 reviews
speaking.app

AI public speaking and interview practice. Record or upload yourself, get feedback on pacing, filler words, structure, and clarity, and have your answer rewritten into proven frameworks like STAR and PREP.

Rating
0 reviews
Pricing
Freemium Free trial $8.33 / Monthly (Pro, billed annually)

Which is more popular?

Based on our record, mlsql seems to be more popular. It has been mentioned 2 times since March 2021.

social mentions
2 vs 0
LMS popularity
100% vs 0%
alternatives listed
1 vs 137

Base details

Website, pricing, platforms and company facts side by side.

mlsql
speaking.app
Website github.com speaking.app
Pricing —
Freemium Free trial $8.33 / Monthly (Pro, billed annually) Official pricing
Platforms —
Web PWA
Company — Startup from Ireland · 1 - 9 employees · 2025
Listed in

About mlsql and speaking.app

In their own words, as submitted to SaaSHub.

mlsql
speaking.app

No description of mlsql yet.

speaking.app is an AI-powered public speaking and interview practice platform for individuals, teams, and training programs. Rehearse pitches, job interviews, presentations, and impromptu speaking, and get objective feedback before the real thing. How it works: record or upload a spoken response...

Read more about speaking.app

Features and specs

What each product offers, as listed by its team.

mlsql 0 features
speaking.app 12 features

No features have been listed yet.

  • Speech analysis
    Feedback on pacing (WPM), pauses, filler words, structure, and clarity on every session.
  • Smart Rewrite
    Detects which of 15 speech frameworks (STAR, PREP, Story Arc) your answer follows and restructures it.
  • Pitch analysis
    Maps a startup or investor pitch to 13 investor elements and returns a Strong Yes to Pass verdict.
  • Investor pitch practice
    AI pitch coach for demo day and fundraising: maps your startup or investor pitch to 13 investor elements, grades each, and returns a Strong Yes to Pass verdict.
  • Demo day & accelerator prep
    Rehearse your pitch and practice accelerator interview questions (Y Combinator, Techstars, Antler, 500 Global).
  • Interview question library
    1,400+ questions across 90+ curated sets for specific companies, roles, accelerators, and admissions.
  • AI coaching
    Automated coaching feedback after every practice session.
  • Filler word Ah-Counter
    Free live tap counter for um/ah/like, track a whole room of speakers, no account (speaking.app/practice/filler-counter).
  • Free speech timer
    Full-screen green, yellow, red timing lights. No account needed.
  • Champions Library
    Free public library of famous speeches and pitches analyzed with the same engine.
  • Coaching dashboard
    For teams and cohorts: manage seats, assign practice, and track participant progress.
  • Recording upload
    Analyze uploaded recordings, not just live practice (Pro).

Analysis

An editorial look at what each product does well and who it suits.

mlsql
speaking.app

Overall verdict

  • MLSQL is a solid open-source unified platform that blends SQL with machine learning, making data engineering and ML workflows accessible through a single, declarative language. It's a good choice for teams looking to streamline big data and ML pipelines without switching between multiple tools.

Why this product is good

  • It unifies data processing and machine learning under a single SQL-like syntax, lowering the learning curve for data teams.
  • Built on top of Apache Spark, it leverages a proven distributed computing engine for handling large-scale data.
  • Open-source and actively developed, allowing customization and community-driven improvements.
  • Supports the full ML lifecycle including data preprocessing, training, and deployment within one workflow.
  • Reduces the need to context-switch between separate ETL, analytics, and ML tools.

Recommended for

  • Data engineers and data scientists who prefer SQL-centric workflows
  • Teams working with big data on Apache Spark
  • Organizations wanting to unify ETL and machine learning pipelines
  • Companies seeking an open-source alternative to fragmented ML tooling
  • Analysts looking to build ML models without deep programming expertise

Overall verdict

  • Speaking.app appears to be a niche public speaking/communication skills platform. Without extensive independent reviews or track record data, it's best assessed cautiously—suitable for casual skill-building but not verified as a top-tier professional training solution.

Why this product is good

  • Focuses specifically on public speaking and communication improvement
  • Likely offers structured exercises or courses for skill development
  • May provide a convenient app-based format for practicing on your own schedule
  • Could be useful for beginners wanting low-pressure practice tools

Recommended for

  • Individuals looking for casual, self-paced public speaking practice
  • Beginners wanting to build basic confidence before formal training
  • Users seeking a supplementary tool alongside other speech coaching
  • Those exploring low-cost or free options before investing in premium coaching services

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
mlsql
speaking.app
100% 100%
LMS
0% 0%
0% 0%
100% 100%
100% 100%
0% 0%
0% 0%
AI
100% 100%

Questions & Answers

As answered by people managing mlsql and speaking.app.

What's the story behind your product?

speaking.app's answer:

speaking.app began with a personal realization. Its founder, Bjarte Sunde, an engineer by training, found that in a world increasingly shaped by AI, the skill that mattered most was still an old one: speaking clearly and confidently when it counts. While working on his own communication, he wanted honest feedback and a private way to practice, without an expensive coach and without waiting until the moment had already passed.

The product is built on a simple belief: how you come across in an interview, a pitch, or on stage should not come down to luck or budget. Everyone deserves a place to rehearse, hear how they actually sound, and improve before it matters. What began as a personal tool is now used by individuals, founders, students, and organizations to turn high-stakes speaking from something you hope goes well into something you have prepared for. Built in Dublin by Prosody Ltd, speaking.app is working toward a future where confident communication is something anyone can develop, not a privilege of the few.

What makes your product unique?

speaking.app's answer:

speaking.app analyzes both how you speak and what you say, then coaches you until it becomes second nature.

  • Delivery analysis on every session: pacing (words per minute), pauses, filler words, and clarity.
  • Smart Rewrite detects which of 15 speech frameworks (such as STAR or PREP) your answer is closest to, scores how well you follow it, and rewrites it in that structure.
  • Founder pitch analysis maps a startup or investor pitch to the 13 elements investors listen for, rates each, and returns an investor-style verdict from Strong Yes to Pass.
  • Coaching feedback after every session tells you what to work on next, so each practice run has a clear focus.

Most tools stop at delivery metrics. speaking.app tells you what to fix, shows you how, and helps you rehearse it until it sticks.

Why should a person choose your product over its competitors?

speaking.app's answer:

Choose speaking.app because it does more than measure your delivery. It helps you fix it and rehearse until you are ready.

  • It goes past delivery metrics. Beyond pacing and filler words, you get structural feedback and an AI rewrite of what you actually said, so you improve the substance, not just the surface.
  • It coaches you, then you iterate. After each session it tells you what to work on next, so every practice run has a focus and progress compounds.
  • It is built for specific, high-stakes moments. A dedicated pitch analysis for founders (the 13 elements investors listen for, with a verdict), plus 1,400+ real interview questions for named companies, roles, accelerators, and admissions.
  • It works solo or across a whole program. Practise on your own, or run a cohort from a coaching dashboard (accelerators, universities, coaching firms).

It is practice software for getting genuinely better beforehand, not a live in-call copilot.

How would you describe the primary audience of your product?

speaking.app's answer:

speaking.app is for people with a high-stakes speaking moment coming up, and the organizations that train them.

  • Individuals: job seekers rehearsing interviews, startup founders preparing pitches and demo day, and professionals practising presentations and public speaking.
  • Organizations running structured practice programs: accelerators, universities, and coaching firms that use a coaching dashboard to manage participants and track progress.
  • Toastmasters and clubs: members use the free filler-word Ah-Counter and speech timer to run and time their meetings, no account needed.

Which are the primary technologies used for building your product?

speaking.app's answer:

speaking.app is a modern web application. There is nothing to download or install.

  • Proven, industry-standard stack: Next.js and React on the front end, Python (FastAPI) on the back end.
  • AI at the core: speech is transcribed with AI speech-to-text; the analysis, coaching feedback, and Smart Rewrite are powered by large language models.
  • Runs anywhere: works in any browser as a Progressive Web App (PWA), installable on any device.

User comments

Share your experience with using mlsql and speaking.app. For example, how are they different and which one is better?

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Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

mlsql 2 mentions
speaking.app 0 mentions
  • Download the files from Docker Container and locally edit them
    I am working on a project that requires me to take user input (as English) and return SQL queries. We will eventually be working with multiple datasets, which is why the valuenet over at https://github.com/paulfitz/mlsql ended up being... Source: over 4 years ago
  • Clone and edit Docker Projects hosted on Github
    I found this great resource here: https://github.com/paulfitz/mlsql. Source: almost 5 years ago

Tracking speaking.app since Jan 2026.

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