B2B SaaS Provider · Data Provider / Broker · vs · B2B SaaS Provider

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Scale AI vs Together AI

Structured technology and market comparison · 2026

Direct Feature Comparison

Scale AI · vs · Together AI
Market Cluster / Sector
Scale AIB2B SaaS Provider · Data Provider / Broker
Together AIB2B SaaS Provider
Platform Focus
Scale AI

Enterprise AI data, evaluation and deployment platform.

Together AI

Open-source AI cloud for training, inference and GPU compute.

Company Size
Scale AI501–1,000 employees
Together AI201–500 employees
Headquarters
Scale AIUS
Together AIUS
Year Founded
Scale AI2016
Together AI2022

Analyze all overlapping signals and tech stacks for Scale AI and Together AI

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Comparison Analysis

What is the main difference between Scale AI and Together AI?

When comparing Scale AI and Together AI, both platforms operate within the Cloud Data Warehouse / Data Lake, B2B SaaS Provider, and Large Language Models (LLM) & AI ecosystem. Scale AI is positioned as Enterprise AI data, evaluation and deployment platform, whereas Together AI focuses on Open-source AI cloud for training, inference and GPU compute. Decision-makers evaluate both solutions when orchestrating their commercial monetization and technology stack.

What are the top alternatives to Scale AI and Together AI?

When evaluating Scale AI and Together AI, enterprise buyers also consider other platforms in Cloud Data Warehouse / Data Lake, B2B SaaS Provider, and Large Language Models (LLM) & AI. You can discover the full competitive landscape and evaluate other alternatives by viewing their respective footprint profiles on Polaris7.

How do the corporate scale, structure, and headquarters of Scale AI and Together AI compare?

Scale AI is headquartered in US (founded in 2016) with 501–1,000 employees. Together AI is based in US (founded in 2022) with 201–500 employees. Complete ownership, subsidiary trees, and corporate affiliations are documented across Polaris7.

Market Signals

Recent Market Signals & Activity: Scale AI vs Together AI

Documented market movements, strategic partnerships, product releases, and regulatory developments mapped across Polaris7.

SC

Scale AI

Recent Signals

  • ·techcrunchPlatform

    Meta launches AI-focused subscription plans

    Meta has launched Meta One, a unified subscription service bundling premium features across Instagram, Facebook, WhatsApp, and Meta AI, now globally available. Core functions remain free, while the subscription offers extended AI usage, enhanced self-expression tools, and professional solutions for creators and businesses, gradually rolling out to apps like Edits and AI glasses. Over 15 million subscriptions and trials have been recorded. Pricing starts at $2.99/€2.49 per month for individual app-plus plans, with bundled Core and Premium tiers at $7.99 and $19.99 (€6.99 and €16.99) monthly, and business plans ranging from $14.99 to $499 (up to €549) per month. This initiative aligns with Meta's AI monetization strategy, following a $14.3 billion investment in Scale AI and planned infrastructure spending exceeding $600 billion by 2028. Early revenue data shows Instagram at $1.2 million daily and Facebook at $528,000 as of September 9, 2026, though the launch faces regulatory scrutiny and industry warnings about AI risks.

    • Meta One is a unified subscription service for Instagram, Facebook, WhatsApp, and Meta AI, globally available, launched on September 16, 2026.
    • Over 15 million subscriptions and trial activations have been recorded from earlier tests.
    • Pricing starts at $2.99/€2.49 per month for individual app-plus plans; bundled Core and Premium cost $7.99/€6.99 and $19.99/€16.99 respectively.
  • ·CNBC TechnologyAI Agents

    Meta Launches Paid Personal AI Agent App 'Muse' Amid Privacy Scrutiny

    Meta launched Muse, a personal AI agent, on September 8, 2026, initially in the US, with availability across web, iOS, Android, and WhatsApp, and now expanded to Mac desktop. Powered by the Muse Spark 1.3 model, Muse autonomously handles tasks like emailing, travel booking, purchases, organizing files, filling forms, and summarizing messages. It operates in a secure VM per user, with a Sentinel agent approving sensitive actions, and integrates with Messages, Calendar, and Notes. Payments are processed via Stripe's Link, with integrations like Shopify Shop Pay and 1Password. The service offers a free tier (up to 100 million tokens weekly) and paid plans, including Meta One starting at $20 or 2.49 Euros monthly, with a $100 premium option. Despite privacy concerns and an up to $18 billion settlement over addictive design, Meta asserts user data isn't used for ads, focusing on commerce monetization. A confidential VM with user-held encryption keys is planned for later this year.

    • Meta launched Muse on September 8, 2026, as a personal AI agent, initially in the US, across web, iOS, Android, WhatsApp, and now Mac desktop.
    • Muse is powered by Muse Spark 1.3, and can handle tasks like emailing, travel booking, purchasing, file organization, form filling, and summarizing messages, with integrations for Messages, Calendar, and Notes.
    • Muse operates in a secure VM per user with Sentinel agent approval; payments use Stripe's Link, with a free tier (up to 100M tokens/week) and paid plans starting at $20/month (Meta One) or 2.49 Euros, plus a $100 option.
TO

Together AI

Recent Signals

  • ·Together AI

    Introducing Together Link: Run open models inside the harness you already use

    Together AI announces Together Link, a new product that allows running open models within existing harnesses, alongside new research blog posts on ThunderKittens for NVIDIA Vera Rubin NVL72, ThunderAgent, and ICML 2026 participation.

  • ·techcrunchAI

    Open or Closed AI: Founders' Choices at TechCrunch Disrupt 2026

    The article previews upcoming discussions at TechCrunch Disrupt 2026 (Oct 13-15, San Francisco) on AI model strategy. It highlights how startups increasingly use multiple models—open and proprietary—for different tasks, weighing cost, performance, and flexibility. Sessions feature leaders from Together AI, Pathway, Oumi, Nvidia, and Ricursive Intelligence. Topics include whether to build, customize, or rent AI models, optimizing AI hardware (chip design), and trade-offs between frontier APIs (like OpenAI, Google) and open-weight models. The article emphasizes that model choice shapes product differentiation, infrastructure needs, and long-term business viability. It's a conference promotion with substantive insights on AI architecture decisions.

    • TechCrunch Disrupt 2026 takes place Oct 13-15 at Moscone West, San Francisco.
    • The conference features 200+ sessions, 250+ speakers, and 300+ exhibiting startups.
    • Sessions cover multi-model strategies, custom model development, and AI-designed hardware.
  • ·Aakash GuptaAI-Native Product Management

    Together AI Product Team Shares AI-Native Workflow Stack

    Together AI's product team, including CPO Charles Zedlewski and PMs Necoline Hubner and Pavneet Ahluwalia, outlined their AI-native product development stack in a podcast. The stack comprises four components: a shared context repository accessible by any AI harness, skills for feature research and PRD writing, an orchestrator for leadership, and agent evals. The team emphasizes collective productivity over individual gains, using multiple models like GLM and Kimi instead of relying solely on Anthropic. They validate products through agent-based tests, checking if AI agents can complete tasks using their documentation and API. The article also highlights Together AI's $8.3 billion valuation from its Series C round.

    • Together AI is valued at $8.3 billion.
    • Together AI's product team uses a four-component AI-native stack: shared context repo, skills, orchestrator, and agent evals.
    • The team uses multiple AI models (e.g., GLM, Kimi) rather than only Anthropic's models.

Compare their exact ecosystem overlaps.

Explore all deep relationships in Polaris7. Discover exactly which mutual clients, integrated technologies, and overlapping partners Scale AI and Together AI share across the market ecosystem.