up to 40x
Cost Reduction
One-Time Frontier Cost: Expensive frontier models are called strictly once to reason through a novel task, resolve edge cases, and compile the logic into a reusable procedural skill.
Low-Cost Execution: Subsequent requests completely bypass the frontier model, routing instead to lightweight, small models that execute the pre-compiled memory trace.
Smart Routing
Delegating trivial requests to small models, while preserving frontier models for complex tasks.
Standard AI agents re-reason every step from scratch, wasting millions of expensive frontier tokens on repetitive prompts and tools.
Analog integrates out of the box with your preferred AI infrastructure:
OpenAI, Anthropicm OpenRouter, Ollama, etc: Access 200+ models with unified billing and fallback routing.
Enterprise and power-user workflows demand verifiable compliance and debugging:
Step-by-Step Thought & Tool Tracing: Inspect the complete tree of reasoning steps, tool calls, and API responses in real-time.
Distillation & Skill Audit: Review distilled procedural skills before they become automatic routines.
Complete Audit Trail: Export and review structured session logs with token utilization, exact costs, and latency metrics per query.
Multi-Tenant & Agent Isolation: Maintain dedicated workspace history and memories isolated per agent and project.
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Remembers FactsLong term knowledge update and symbolic reasoning -
Remembers ExperiencesRemembers what did user ask, what agent did, what was overall experience -
Remembers ProceduresRemembers how did agent use tools on multi-step workflows, uses smaller models on learned procedures
Powered by Analog’s proprietary dual-engine architecture:
DeepThink (Cognition & Memory):
Remembers Facts & Knowledge: Continuous symbolic graph updates with temporal and spatial awareness.
Hypothetical & Contradiction Reasoning: Handles multi-hop if-else branches, checks hypotheses, and resolves contradictory facts over time.
DeepAct (Execution & Skill Distillation):
Remembers Experiences & Procedures: Retains what happened, what the user requested, and which tool sequences succeeded.
Benchmark Proven: Outperforms traditional vector RAG and leading semantic memory systems on Microsoft State-Bench (70.7%), HotPotQA (91%), and BEAM (59.2%).
