Analog AI is an agentic orchestration infrastructure designed for long-horizon agents. By integrating a deep-reasoning engine with persistent long-term memory, it enables agents to learn and refine skills, maintain cross-session context, and adapt autonomously to complex, evolving business objectives.
  • 1x
    Reasoning efficiency or frontier models per compute unit
  • ~3x
    Reasoning efficiency of Analog AI per compute unit
01
User
Sends a message
Incoming
02
AI agent
Understands & asks clarifying questions
Thinking…
03
User
Reviews
Reviewing
04
Final Response
Sent back
Delivered
05
Knowledge
Knowledge improves
+1 insight
↻ loop continues — knowledge grows with every supervised conversation
0
Messages handled
–
Accuracy
–
Avg response
  • Explainability
    Deep common sense reasoning, making the AI decisions explainable
  • Self-learning
    AI agents self learn by user interactions
  • Human in the loop
    Asking you for help, when lacks the knowledge
Long horizon orchestration
Begins with foundational knowledge and continuously adapts to the noisy flow of everyday information.
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
Understanding of time and location
Understanding, that certain facts are not generally true, but true for the certain time and location
Skill learning
Automatically learns skills under your supervision
Analog Cloud
Create customer facing agent, share documents and supervise. Best for the short term events, where active learning is critical
Try Now
Use our agentic tool, create your customer facing agents, ingest private documents, audit reasoning logic of the past conversations.
See demo >
Partners & Supporters
Made on
Tilda