Foundation Models & Agent Frameworks · B2B SaaS Provider
TypeSafe AI
Machine-native AI models for confidence-aware software automation.
Available information varies by company and source.
Profile record updated:
Company facts
- Official name
- TypeSafe AI, Inc.
- Entity type
- COMPANY
- Headquarters
- United States
- Company size
- 10–49
- Market cluster / sector
- Foundation Models & Agent Frameworks
- Market role
- B2B SaaS Provider
- Official website
- typesafe.ai
What TypeSafe AI does
TypeSafe AI operates a proprietary hosted-model infrastructure business. It provides Jev through an API and console, enabling customers to embed structured classification and confidence-aware decisioning into software applications. Value is created by making model outputs directly actionable in automated workflows, while retaining human review for low-confidence decisions. Revenue scales with customer API input-token consumption.
Category differentiation
TypeSafe AI is a hosted AI-model infrastructure provider, not the TypeScript library or a general-purpose software type-safety tool. It focuses on typed, confidence-aware automated decisions rather than open-ended conversational AI.
Strategic context
AI-supported assessment from the existing company research; distinguish interpretation from sourced facts.
TypeSafe AI, Inc. is a United States-based private AI infrastructure company developing machine-native models for automated software workflows. Its first public model, Jev, accepts structured questions and returns typed decisions, calibrated probabilities and confidence estimates rather than free-form text. Software can automatically execute high-confidence actions and route uncertain cases to human review. The company sells hosted API access to software developers, engineering teams and businesses building automated decision systems. Jev is monetised through usage-based token pricing: TypeSafe AI publishes a price of $42 per billion input tokens and does not separately meter output tokens.
Company news briefing
Briefing updated:
TypeSafe AI has secured an $870 million investment led by Andreessen Horowitz at a $7.5 billion valuation, crossing $100 million ARR within its first week. The company's Jev decision model has achieved rapid ecosystem adoption, powering workflows across Vercel and Aurora Mobile's GPTBots.ai. This market traction has catalysed wider industry validation, prompting competitors such as OpenAI and Amazon to release corresponding decision-model APIs and open-source alternatives.
Business model & monetisation
TypeSafe AI monetises hosted API access to Jev on a usage-based infrastructure model. The published price is $42 per billion input tokens, with output tokens provided without a separate meter. The commercial model is metered API consumption rather than advertising, consumer subscriptions or professional-services retainers.
- Jev hosted API input-token usage
- Pay-per-use metered API pricing
Products & capabilities
No products with linked sources are available in this view.
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Competitors & alternatives
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AI SaaS and APIs for decisions, multimodal analysis, and chat.
LLM developer offering AI chat and API access.
Enterprise AI platform for secure language models and deployments.
Foundation model company selling AI assistants and model APIs.
Frontier AI models, developer tools and enterprise agent platform.
Side-by-side comparisons
Recent recorded signals
Dates refer to the source publication. Older entries are historical context, not evidence of a new event.
The Crunchbase Unicorn Board Tops 1,900 Companies In October, With 34 Companies Joining — Half Under 4 Years Old
Product & Platform Launch · Recorded impact score: 3/5
In October 2026, 34 companies joined the Crunchbase Unicorn Board, adding over $96 billion in value and $14.8 billion in total funding, bringing the total to a record 1,900 private companies, including over 1,000 U.S.-based unicorns. Half of the new unicorns are less than 4 years old, with nine achieving unicorn status via seed or Series A rounds, reflecting the rapid pace of the AI cycle. Leading industries included frontier labs, agentic AI, aerospace, and semiconductors, with the U.S. contributing 23 companies, followed by China and Korea with three each. Notable new unicorns include TypeSafe AI ($7.5B valuation), Manus AI ($4B), and Axiom Solutions International, with top investors like Andreessen Horowitz, Sequoia Capital, and General Catalyst backing the cohort.
- 34 companies joined the Crunchbase Unicorn Board in October 2026, adding over $96 billion in value and $14.8 billion in funding.
- The board reached a record 1,900 private companies, including over 1,000 U.S.-based unicorns.
A Jev that can ask Opus for help gives Opus accuracy at 4x lower cost
Product & Platform Launch · Recorded impact score: 3/5
Hightouch published a technical blog post on November 4, 2026, detailing experiments using LLM judges to evaluate identity resolution results. They benchmarked decision models Jev (from TypeSafe AI) and GPT-6 Luna (OpenAI) against frontier models like Claude Opus, Gemini 3.1 Pro, and GPT-6 Sol. While Luna outperformed Jev out of the box (97.3% vs 95.6% accuracy on an easier test), Jev's better confidence calibration enabled a hybrid approach (Jev first, then Opus for uncertain cases) to achieve 98.8% accuracy on the easier test and 95.3% on a harder test, nearly matching Opus alone (99.0% and 95.1%) at a fraction of the cost ($0.88 vs $3.86 per 1,000 identities on the easier test). The hybrid Jev approach proved more robust on harder cases than hybrid Luna (95.3% vs 91.6% accuracy), demonstrating that calibration matters more than raw out-of-the-box performance.
- Hightouch tested LLM judges for identity resolution, comparing decision models Jev and GPT-6 Luna against frontier models like Claude Opus.
- On an easier benchmark, Luna achieved 97.3% accuracy vs Jev's 95.6%, but Jev's confidence calibration was superior.
Vercel AI Gateway Shows Jev Fastest Adopted Model
AI & LLM · Recorded impact score: 4/5
According to data published by Vercel, its AI gateway shows that Jev, a decision model from TypeSafe AI, reached 35% usage among paid teams within two weeks of launch, making it the fastest-adopted model in Vercel's history. Jev is designed for efficient classification by choosing from limited outputs. The data also indicates that open-source models now account for over 70% of tokens processed and nearly 25% of spend through the gateway, while spending on frontier labs has grown tenfold, suggesting complementary growth. Vercel itself adopted Jev to replace GPT-6 Luna for classifying harmful commands. The report provides first concrete usage data amid buzz around decision models, with OpenAI and Amazon releasing competing models.
- Jev reached 35% usage among paid teams within two weeks of launch.
- Jev is nearly double the reach of the second most popular model, Sonnet 5.5.
Kochava Product & Partnership Updates Bulletin: Q3 2026
Product & Platform Launch · Recorded impact score: 2/5
Kochava has released its Q3 2026 product and partnership updates bulletin, headlined by a new measurement integration with OpenAI's ChatGPT Ads across mobile and web. The company also rolled out major SDK upgrades (iOS v11.0.0 and Android v7.0.0) alongside agentic advertising tools, including the Ads MCP Server from Meta and TypeSafe AI's Jev model inside StationOne.
- Integration with OpenAI's ChatGPT Ads went live in Q3 2026 across iOS, Android, and web.
- Released major SDK updates, including iOS SDK v11.0.0 and Android SDK v7.0.0, introducing automated click identifier capture and dual-stack IPv4/IPv6 support.
a16z Leads Investment in TypeSafe AI, Creator of Jev
AI · Recorded impact score: 4/5
Andreessen Horowitz (a16z) led an $870 million investment in TypeSafe AI at a $7.5 billion valuation, with participation from Sequoia and DCVC. TypeSafe develops Jev, a non-text AI model that outputs calibrated decisions, bypassing text parsing. Launched September 15, Jev quickly gained traction, generating one trillion tokens in three days and being adopted by a third of Fortune 500 companies within a week. It is faster and cheaper than frontier LLMs, ideal for automation. This investment signals a16z's focus on AI that enhances software development. TypeSafe crossed $100M ARR in its first week, and the $7.5B valuation came just three weeks post-launch. The announcement also highlights the rise of decision models as a category, with OpenAI, Microsoft, Perplexity, Cloudflare, and others releasing their own versions. Co-founded in 2024 by ex-OpenAI researcher Diogo Almeida, ex-Meta engineer Sasha Sheng, and Erik Gafni.
- a16z led a $870 million investment in TypeSafe AI at a $7.5 billion valuation, with Sequoia and DCVC participating.
- Jev, a non-text AI model, generated 1 trillion tokens in 3 days post-launch and was adopted by a third of Fortune 500 companies within a week.
Careers & open positions
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| Position | Department | Location | Posted |
|---|---|---|---|
| Safety Jevroni (Contract, 6 weeks)(Senior) | Member of Technical Staff | San Francisco Office | |
| Strategic Finance(Mid-Level) | Operations | San Francisco Office | |
| Founding Recruiter(Senior) | Operations | San Francisco Office | |
| Community Manager(Mid-Level) | Operations | San Francisco Office | |
| Developer Advocate(Mid-Level) | Member of Technical Staff | San Francisco Office |
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Questions about TypeSafe AI
What is TypeSafe AI?
TypeSafe AI is an AI infrastructure company building machine-native models that return typed decisions, probabilities and confidence estimates for software automation.
Who uses TypeSafe AI?
Software developers, engineering teams, AI application builders and businesses building automated decision workflows use TypeSafe AI.
How does TypeSafe AI make money?
TypeSafe AI charges for hosted Jev API usage, publishing a price of $42 per billion input tokens while not separately metering output tokens.
Sources & coverage
This profile uses public, official and technically observable information. Missing information does not prove that a product or relationship does not exist. The list below does not imply that every profile statement has been verified.
5 publicly documented primary sources and citations linked across the market graph.
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