Cryo
Cryo is a programming language from Endothermic Labs designed for building AI agents and workflows that run indefinitely. Programs execute on the Freeze/Thaw Virtual Machine (FTVM), which pauses and resumes execution without losing state, eliminating manual serialization and recovery logic. Cryo includes typed LLM plugins for text classification and scoring, pre-built integrations with GitHub, Hacker News, and chatrooms, and concurrency primitives like coroutines and pipes for composing multi-task agent logic. Developers can prototype in the in-browser Cryo Playground before deploying to production.
Cryo is an AI agent, priced at $1 a month on the Cryo Playground plan, integrating with GitHub, Hacker News and Cloudflare. InnovaAI rates it 1.3 of 10 for agency adoption, best for Developer, CTO/Founder and Operations Engineer roles.
Agency Audit
Cryo is a programming language purpose-built for long-running AI agents and workflows that can pause and resume indefinitely via the Freeze/Thaw Virtual Machine. It connects to external services like GitHub, Hacker News, and chatrooms through typed plugins, and supports concurrent agent logic with coroutines and pipes. Adopt Cryo if your agency has in-house developers who spend significant time building custom automation, monitoring workflows, or integrating AI agents into client operations. The payoff is fastest for engineering-led shops where developers currently hand-code agent infrastructure in general-purpose languages.
3recommended
72/mo
$5,399/mo
High
Illustrative scenario. Not a guarantee. Net capacity is the value of reclaimed time at $75/hr, less the lowest verified paid base plan (flat plan cost is shared). Hours saved come from the service estimate; implementation, taxes, and unprovided usage charges are excluded.
- Developer handling building custom AI agents
- CTO/Founder handling long-running workflow automation
- Operations Engineer handling monitoring and data collection
- Your agency has no in-house developers or relies entirely on no-code automation platforms, because Cryo is a programming language and offers no value to non-technical roles.
- Your team's automation needs are one-off scripts or short-lived tasks, because Cryo's freeze/thaw model and FTVM overhead are overkill for work that runs once and exits.
- Your developers are already deeply invested in Python or JavaScript agent frameworks and have no appetite for learning a new language, because the switching cost outweighs the FTVM benefits for small teams.
Internal Adoption Path
$1/mo
$1/mo flat plan
72 hr/mo
3 seats × 24 hr each
$5,400/mo
modeled at $75/hr labor rate
$5,399/mo
value − subscription cost
In this model, 3 seats reclaim 72 hours of team time each month. Valued at $75/hr that is $5,400/mo, and after the $1/mo subscription it leaves $5,399/mo of capacity for billable client work.
Illustrative scenario. Not a guarantee. Uses the lowest verified paid base plan. Implementation, taxes, and unprovided usage charges are excluded.
Platform Features
Core capabilities of Cryo
Freeze/Thaw Virtual Machine (FTVM)
Programs pause and resume without losing execution state, allowing long-running agents to survive restarts or network interruptions. Developers no longer manually serialize and restore agent memory, cutting boilerplate code for monitoring and background-task workflows.
Typed LLM plugins (Jev)
Classify and score text using LLM calls with type-safe output, reducing the parsing and validation work developers do after calling language models. Useful for agents that filter content, route messages, or make decisions based on text analysis.
Service integrations (GitHub, Hacker News, chatrooms)
Pre-built plugins connect agents to external APIs without writing raw HTTP clients. Developers can focus on agent logic instead of authentication, pagination, and error handling for each service.
Coroutines and concurrent composition
Build multi-task agents using coroutines, select, and pipes instead of callbacks or async/await. Reduces cognitive load for developers orchestrating parallel workflows like monitoring multiple data sources simultaneously.
In-browser Cryo Playground
Run and test Cryo programs directly in a browser without local setup, lowering the barrier for developers to prototype agents before deploying to production. Useful for rapid iteration on agent logic.
Indefinite execution model
Programs designed to run continuously without explicit termination, eliminating the need for external job schedulers or cron infrastructure. Operations teams can deploy a single Cryo program to handle ongoing monitoring or data collection.
What Makes Cryo Different
Unique advantages vs similar tools in this niche
Freeze/thaw VM keeps agents running indefinitely across waits
vs Conventional runtimes that must restart or poll to stay aliveThe Freeze/Thaw Virtual Machine is built to keep a program going for an indefinite period of time.
Typed LLM classification with compile-checked match arms
vs Unstructured prompt-based classificationJev classifies text into a type you declare, so the answer can only be one of its members and a match on it is checked for every case.
Value Equation
Outcome-likelihood-time-effort assessment for Cryo
Limited agency channel
Cryo scored below the agency-resellability threshold (agency_fit_score < 50). The Value Equation projects agency-side outcomes, which don't apply to tools without a clear resell pathway.
Contact CryoPricing
Cryo platform cost to your agency
Cryo Playground: $1/mo
Cryo Playground
- This playground runs a small version of Cryo right in your browser, along with some example plugins you can use from your programs.
- from plugin "hn" import { HN };
- from plugin "jev" import { noul };
- var stdio = stdio!();
No verified white-label program for Cryo: client-facing delivery runs under the platform's native branding.
Market Intelligence
Offer + scale economics for Cryo
Limited agency channel
Cryo scored below the agency-resellability threshold (agency_fit_score < 50). It's a useful tool but not designed for white-labeled or retainer-based reselling, so we don't publish productized offer economics for it.
Contact CryoInvestment Decision Framework
Strategic vetting analysis for Cryo
Skip
Weak agency-resell fit
Buy If
4Your Founder or CTO oversees multiple concurrent automation projects and needs developers to compose agent logic without managing threading or async callbacks, since Cryo's coroutines and select primitives flatten that complexity.
Your in-house developers spend 8+ hours per week building custom AI agents or monitoring workflows that need to pause and resume without losing state, because Cryo's FTVM eliminates manual state-management code.
Your team integrates AI agents with GitHub, Hacker News, or chatroom APIs regularly, because Cryo's typed plugins reduce boilerplate integration work compared to writing raw API clients.
Your Operations team runs long-running monitoring or data-collection tasks that currently require external job schedulers or cron infrastructure, because Cryo programs can run indefinitely on FTVM without external orchestration.
Skip If
4Your developers are already deeply invested in Python or JavaScript agent frameworks and have no appetite for learning a new language, because the switching cost outweighs the FTVM benefits for small teams.
Your agency has no in-house developers or relies entirely on no-code automation platforms, because Cryo is a programming language and offers no value to non-technical roles.
Your team's automation needs are one-off scripts or short-lived tasks, because Cryo's freeze/thaw model and FTVM overhead are overkill for work that runs once and exits.
Your agency does not integrate AI agents into client deliverables or internal workflows, because Cryo solves a problem you do not have.
Bottom Line
Cryo is a programming language purpose-built for long-running AI agents and workflows that can pause and resume indefinitely via the Freeze/Thaw Virtual Machine. It connects to external services like GitHub, Hacker News, and chatrooms through typed plugins, and supports concurrent agent logic with coroutines and pipes. Adopt Cryo if your agency has in-house developers who spend significant time building custom automation, monitoring workflows, or integrating AI agents into client operations. The payoff is fastest for engineering-led shops where developers currently hand-code agent infrastructure in general-purpose languages.
Reality Check
Cryo requires your team to learn a new language and mental model around freeze/thaw execution, which adds onboarding friction compared to extending existing Python or Node.js codebases. ROI is highest only if your developers are already building agents or long-running workflows; teams using off-the-shelf tools will see minimal benefit.
High effort: requires technical configuration and team training
Academy for Cryo
Work through it in order: the course for this service first, then the modules behind it.
Course for this service
Cryo Agency Implementation, Building Autonomous AI Agent Services
Learn how to architect and deliver long-running AI agent workflows for clients using Cryo's Freeze/Thaw Virtual Machine and typed LLM plugins. This course covers productizing agent development, managing client deployments across GitHub and chatroom integrations, and structuring retainer pricing around agent monitoring and optimization.
Open the courseNo Academy modules are published for this service yet. Browse the full Academy
Why this category matters
The commercial case before the tooling.
Core concepts
The mental model you need to price and scope the work.
- Wiring Over WidgetsConcept
The AI agent itself is a commodity, but the value for agencies lies in the integration layer: connecting a pre-built agent to a client's CRM, calendar, and review cycle. This framework shifts focus from selecting the 'best' agent to mastering the wiring process. For example, an agency using Vendasta's white-label AI receptionist for a local business must configure it to match the client's booking rules and follow-up cadence, turning a generic tool into a tailored service. As agentic AI adoption grows (77% of decision-makers now run agents in production), clients expect this customization. Agencies that treat agents as components and invest in repeatable wiring processes can charge retainers for ongoing optimization, rather than one-off setup fees.
- Wiring Over WidgetsConcept
The AI agent market sells finished workers, but the strategic value for agencies lies not in the agent itself, which is increasingly a commodity, but in the wiring that connects it to a specific client's CRM, calendar, and review cycle. This framework, 'Wiring Over Widgets,' argues that agencies that treat agents as components rather than products win. The agent is the widget; the wiring is the integration, customization, and ongoing optimization that turns a generic tool into a tailored solution. For example, a white-label platform like Vendasta provides AI employees, but the agency's role is to configure them for each local business's unique lead flow and follow-up process. This wiring is where retainer pricing originates, as it requires ongoing maintenance and adjustment. Recent research shows that 88% of B2B marketers face foundational gaps, meaning clients need help not just deploying agents, but ensuring their operations can support them. Agencies that master the wiring can charge a premium for the irreducible value they add.
- Wiring Premium Over Agent CommodityConcept
Pre-built agents are converging on the same underlying model capability, so the agent itself prices toward zero. What holds value is the wiring: the mapping of a specific client's CRM fields, calendar rules, escalation paths, and review cadence into the agent's loop. Agencies that sell the agent as the product compete on seat price against every reseller of the same worker. Agencies that sell the wiring charge for discovery, field mapping, exception handling, and monthly tuning, which is retainer work. Vendasta's white-label AI workforce and Relevance AI's pre-built sales agents both arrive configured out of the box, which means the configuration is not the moat; the client-specific plumbing is. A practical test: if a competitor could swap your agent vendor next quarter without the client noticing, you sold a commodity. If the swap would break their CRM hygiene, approval chain, or reporting, you sold wiring.
Decision and risk
How to judge the fit, and the ways it goes wrong.
- AI Agents Rule: Wire the Agent, Not the ProductEvaluation Rule
Treat the AI agent as a commodity component and focus your value on the integration into the client's specific workflows, systems, and review processes.
- AI Agents Rule: Wire the Agent, Not the ProductEvaluation Rule
Treat the AI agent as a commodity component and charge for the integration into the client's specific systems and workflows.
- The Productized Agent Trap: Why AI Agent Services Stall Without Client-Specific WiringFailure Pattern
- The Demo-to-Retainer Gap: Why AI Agents Stall After the Pilot CallFailure Pattern
8 modules selected for Cryo
Frequently Asked Questions
Answers about pricing, setup
Cryo is a programming language for building long-running AI agents and workflows that run on the Freeze/Thaw Virtual Machine (FTVM). Programs can pause and resume indefinitely without losing state, and connect to external services like GitHub, Hacker News, and chatrooms via typed plugins. Developers compose concurrent agent logic using coroutines and pipes, reducing boilerplate compared to general-purpose languages.
Cryo lists 1 plan; the paid price is $1 a month (Cryo Playground).
In-house developers building custom AI agents or long-running workflows see the most direct payoff, because Cryo eliminates manual state management and threading complexity. Your CTO or Founder overseeing multiple automation projects benefits from easier agent composition. Operations teams running continuous monitoring tasks gain value from indefinite execution without external schedulers. Client-facing strategists or account executives do not directly use Cryo but benefit when developers ship faster.
Conservative estimate is 4 to 8 hours per developer per week, assuming your team is already building agents or long-running workflows. The savings come from eliminating manual state serialization, threading boilerplate, and API client code. Teams building one-off scripts or using no-code platforms will see zero savings.
Yes. Cryo is a new language with unfamiliar syntax and a freeze/thaw execution model. Developers familiar with Python, JavaScript, or Go will need 1 to 2 weeks of hands-on practice before shipping production code. The in-browser Playground accelerates learning by letting developers experiment without local setup.
Cryo is best suited for custom agent development and long-running workflows. If your team relies on no-code platforms, off-the-shelf RPA tools, or short-lived scripts, Cryo adds complexity without benefit. It complements existing stacks when you need fine-grained control over agent behavior and state management.
Programs running on the FTVM will stop. Cryo does not publish a data export or migration path, so you should plan to rewrite critical workflows in another language before canceling. Treat Cryo as a long-term commitment for production agents.
Cryo programs run on the FTVM, which Endothermic Labs hosts. The Playground runs in-browser; production deployment details are not published. Contact Endothermic Labs to discuss integration with your deployment pipeline, version control, or monitoring tools.