Meeting BaaS (formerly Spoke.ai) vs SciSpace (formerly Typeset)

In the battle of Meeting BaaS (formerly Spoke.ai) vs SciSpace (formerly Typeset), which AI Summarizer tool comes out on top? We compare reviews, pricing, alternatives, upvotes, features, and more.

Which one is better? Meeting BaaS (formerly Spoke.ai) or SciSpace (formerly Typeset)?

Upon comparing Meeting BaaS (formerly Spoke.ai) with SciSpace (formerly Typeset), which are both AI-powered summarizer tools, SciSpace (formerly Typeset) is the clear winner in terms of upvotes. SciSpace (formerly Typeset) has 24 upvotes, and Meeting BaaS (formerly Spoke.ai) has 6 upvotes.

Feeling rebellious? Cast your vote and shake things up!

Meeting BaaS (formerly Spoke.ai)

Meeting BaaS (formerly Spoke.ai)

What is Meeting BaaS (formerly Spoke.ai)?

Meeting BaaS sends bots into Zoom, Google Meet, and Microsoft Teams calls to record, transcribe, and summarize meetings through a developer API. You POST a meeting URL, the bot joins automatically, and your backend receives recordings, transcripts, speaker diarization, and metadata via webhooks.

Recall.ai and similar meeting-bot APIs charge enterprise rates with opaque pricing. Meeting BaaS starts free with 8 hours of recording and scales at $0.35 per hour on pay-as-you-go, with a Speaking Bots API that streams audio to your LLM in real time so the bot can respond during the call rather than only after it ends.

SaaS teams, sales intelligence platforms, and internal tooling groups use Meeting BaaS to build AI meeting assistants, automate post-call summaries, and analyze customer conversations at scale. The TypeScript SDK, MCP tools, and self-hosting option let you embed meeting capture without building bot infrastructure from scratch.

SciSpace (formerly Typeset)

SciSpace (formerly Typeset)

What is SciSpace (formerly Typeset)?

SciSpace, formerly Typeset, is a research workspace where you search a large academic paper index, chat with PDFs, and draft literature reviews with cited sources. The typeset.io URL now lands on scispace.com, which bundles an AI agent, literature review search, paraphraser, citation generator, data extraction, and AI detection in one interface.

General AI chat tools answer from the open web. SciSpace centers the workflow on papers: you can run systematic reviews across 280M+ indexed works, highlight passages for explanations, and move from reading into AI Writer drafts with references. Biomedical Agent, enterprise recruiting, and Chrome or mobile apps extend the same stack for labs and R&D teams.

Graduate students, PhD researchers, and pharma or biotech analysts use SciSpace to screen literature faster, unpack dense PDFs, and produce summaries or manuscripts with traceable citations. The platform reports adoption by 9.6 million researchers and lists SOC 2 compliance on its site.

Meeting BaaS (formerly Spoke.ai) Upvotes

6

SciSpace (formerly Typeset) Upvotes

24🏆

Meeting BaaS (formerly Spoke.ai) Top Features

  • Unified API for Zoom, Google Meet, and Microsoft Teams with one bot deployment call

  • Gladia-powered transcription with speaker diarization and timestamps included

  • Speaking Bots API streams meeting audio to your LLM and speaks replies back live

  • Free tier: 75 bots per day and 8 hours of meeting recording at no cost

  • Webhooks deliver recordings, transcripts, and metadata to your backend automatically

  • TypeScript SDK with v2 client for type-safe bot creation and error handling

  • Self-hosting option when you need full control over meeting data storage

SciSpace (formerly Typeset) Top Features

  • Search and review literature across 280M+ indexed research papers

  • Chat with PDF highlights for plain-language explanations of dense sections

  • SciSpace Agent plus Biomedical Agent for guided research tasks

  • Built-in paraphraser, citation generator, AI detector, and data extraction tools

  • AI Writer and templates for drafting papers with cited sources

  • Chrome extension and mobile app for reading outside the browser tab

  • Premium plans with a 24-hour money-back guarantee on subscriptions

Meeting BaaS (formerly Spoke.ai) Category

    Summarizer

SciSpace (formerly Typeset) Category

    Summarizer

Meeting BaaS (formerly Spoke.ai) Pricing Type

    Freemium

SciSpace (formerly Typeset) Pricing Type

    Freemium

Meeting BaaS (formerly Spoke.ai) Technologies Used

Next.js
React
Chakra UI
Google Cloud
Google Fonts
Webpack
Emotion

SciSpace (formerly Typeset) Technologies Used

Next.js
Google Analytics
Google Tag Manager
Facebook Pixel
Python
Ruby
Discord
Webpack
Tailwind CSS

Meeting BaaS (formerly Spoke.ai) Tags

Meeting Transcription
Meeting Bot API
Speaker Diarization
Webhook Delivery
Zoom Integration
Google Meet
Microsoft Teams
Content Summary

SciSpace (formerly Typeset) Tags

Paper Discovery
Chat with PDF
Research Agent
Citation Tools
Academic Writing
Paper Search
Biomedical Research
Content Summary

Meeting BaaS (formerly Spoke.ai) Average Rating

No rating available

SciSpace (formerly Typeset) Average Rating

4.00

Meeting BaaS (formerly Spoke.ai) Reviews

No reviews available

SciSpace (formerly Typeset) Reviews

Sara Sara
The simulation model validated experimental J-V and external quantum efficiency (EQE) to demonstrate an improvement in perovskite (PSK) solar cell (PSC) efficiency. The effect of interface properties at the electron transport layer (ETL)/PSK and PSK/hole transport layer (HTL) was investigated using the Solar Cell Capacitance Simulator (SCAPS). The interfaces between ETL, PSK, and HTL were identified as critical factors in determining high open-circuit voltage (Voc) and FF. In this study, the impact of two types of interfaces, ETL/PSK and PSK/HTL, were investigated. Lowering the defect density at both interfaces to 102 cm−2 reduced interface recombination and increased Voc and FF.The absorber layer defect density and n/i interface of perovskite solar cells were investigated using the Solar Cell Capacitance Simulator-1D (SCAPS-1D) at various cell thicknesses. The planar p-i-n structure was defined as PEDOT:PSS/Perovskite/CdS, and its performance was calculated. With a defect density of <1014 cm−3 and an absorber layer thickness of >400 nm, power conversion efficiency can exceed 25%. The study assumed a 0.6 eV Gaussian defect energy level beneath the perovskite's conduction band, which has a characteristic energy of 0.1 eV. These conditions produced the same result on the n/i interface. These findings place constraints on numerical simulations of the correlation between defect mechanism and performance
By Rishit