Running high-compute frontier models for every daily task wastes massive amounts of power and compute, keeping enterprise AI from ever reaching scale
Analog AI is an agentic OS that pairs neural models with symbolic reasoning to deliver predictable, auditable workflows. Analog AI features persistent, dynamic memory that memorizes facts, experiences, and procedures to continuously learn over time.
  • Remembers Facts
    Long term knowledge update and symbolic reasoning
  • Remembers Experiences
    Remembers what did user ask, what agent did, what was overall experience
  • Remembers Procedures
    Remembers how did agent use tools on multi-step workflows, uses smaller models on learned procedures
How to use
Integrations
Chat completion API, for easy integration with established harnessing platform OpenClaw, Hermes, etc. and python SDK, for custom solutions built via LangChain, CrewAI, etc.
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3x

Cost Reduction

Frontier model level performance using mainly small models at 1/3 the spend

Analog AI maximizes efficiency with a procedure learning and smart LLM routing engines. By using lightweight models for everyday tasks and reserving high-powered frontier models only for complex reasoning, Analog AI delivers the same results with 3x lower costs across non-critical agentic workflows.
Long horizon think and act
Begins with foundational knowledge and continuously adapts to the noisy flow of everyday information.
Consists of two modules Deepthink and Deepact
Permission handling
Understanding, when something is or isn't allowed
Hypothetical reasoning
Handling multi-hop if-else logic
Deductions and contradiction handling
Inferring new statements based on the existing data and resolving contradictions
Causal reasoning
Making long causal chain, to understand, what leads to the certain outcome
Spatiotemporal reasoning
Understanding, that certain facts are not generally true, but true for the certain time and location
Skill learning
Automatically learns skills under your supervision
Benchmark Results
Better than anyone at Microsoft state-bench and HotPotQA, one of the best at Beam
  • 59.2%
    BEAM
    One of the biggest result on semantic memory solutions
  • 70.7%

    $0.12/task
    Microsoft State-Bench using frontier model
    Bigger than any result at leaderboard
  • 46.0%

    $0.0175/task
    Microsoft State-Bench using small language model
    3x lower cost per task than the most affordable solution at leaderboard
  • 91%
    HotPotQA
    Biggest result, than any memory solution
Research
Analog AI is on the forefront of the research at emotional intelligence and digital human interfaces. Our engine is already capable, to express broad range of emotions (surprise, confusion, excitement, happiness, disappointment, love, confidence, etc).

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Emotional intelligence and digital human interfaces
We believe, that emotions will play a significant role in both human-computer and agent to agent interactions, leading to safe, ethical and clear decisions.
Partners & Supporters
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