AI Agents talk.
Alchemyst helps them listen
A scalable memory-first system that dynamically extracts and retrieves key conversational facts—delivering 20% higher accuracy over SOTA on the PopQA benchmark with 95% reduction in development time.
Benchmarking Alchemyst
Modern AI agents often suffer from high operational costs, limited task completion, and long development cycles—making it difficult to scale AI systems efficiently. Simply fine-tuning LLMs or increasing infrastructure fails to address these bottlenecks at the root.
Alchemyst tackles these challenges head-on with a context-first memory layer and optimized AI infrastructure that drastically reduces cost, boosts performance, and shortens time-to-launch.
Across real-world deployments, Alchemyst has demonstrated:
- ~40% lower interaction cost by sending only relevant context to the LLM
- ~40% reduction in token usage, making AI more affordable to operate
- 95% decrease in dev time — from 6 months to under 2 weeks
- 2.2× revenue increase from agents built on the platform
- 33.7% improvement in task completion, achieving 99.7% success rate
By turning short-term agents into persistent, context-aware systems, Alchemyst empowers teams to go from idea to production-ready AI in days—not months.
Under The Hood
A two-phase memory pipeline that extracts, consolidates, and retrieves only the most salient conversational facts—enabling scalable, long-term reasoning.
Alchemyst delivers a four-stage processing pipeline—Asym0, OKG Orchestration, ThinkRAG, and Context Marketing—connecting Data Sources to Agents/MCPs with comprehensive observability across all stages.
The architecture supports two deployment options: Managed Services leveraging MongoDB and QDrant for rapid deployment by development teams and small companies, and On-Premises Enterprise solutions with multi-source integration for organizations requiring data sovereignty and enhanced security.
This design enables scalable data orchestration while providing deployment flexibility to meet diverse organizational requirements and compliance needs.