Build, deploy, and scale autonomous AI agents with expert human oversight
Memory that reasons
Stage
Established
Not given
Founded
2021
Not given
Based in
US
US
Pricing model
Contact for pricing
Freemium
Pricing
Fixed monthly subscription with custom pricing based on user licenses and needs. No hidden fees, annual subscriptions with monthly payments. 2-day expert-led discovery workshop costs are 100% credited toward subscription pricing.
Free plan at $0 USD; Pro plan at $5 USD per month.
Key features
Enterprise Context Engine™ to structure organizational knowledge for AI decisions
Agentic AI agents that scan, test and act on data on schedule or on demand
No data migration required; connects to existing systems
700+ prebuilt data connectors and integrations
Deployment on AWS, Azure, or GCP with flexible hosting options
Enterprise compliance: SOC 2 Type II, HIPAA, GDPR, ISO 42001
Model-agnostic platform working with existing enterprise infrastructure
Compounding Intelligence where each solution builds on the last
Transparent and auditable workflows with full lineage tracking
Expert-led 2-day discovery workshops with PhD-level data scientists
Entity-graph spreading activation for cross-vocabulary retrieval
Works with any LLM model
No LLM or GPU in retrieval path
Point-in-time and windowed recall
Timestamped memories
Fixed recall cost as memory grows
What makes it different
Hybrid Approach™ pairing agentic AI with human expert oversight for accountability
Production-ready AI in weeks, not months
70% faster from start to go-live year over year
Outcome-based guarantees and PoC engagements for risk-free transformation
Full platform access for unlimited solution creation and deployment
Reaches answers across unrelated documents that share no keywords, where vector search scores zero
Deterministic retrieval with no model in the path, so results never vary between queries
Constant per-query cost regardless of memory size, even at 32,000 words
No infrastructure to run—no vector database, cluster, or GPU needed
Works with any model, so small local models gain the most from better retrieval