Multi-agent scenario engine for Indian market intelligence. Built for capital allocation decisions that compound.
ZenoLattice is a proprietary multi-agent intelligence system — 55 specialized agents analyzing Indian markets through multiple philosophy lenses simultaneously. Like an investment committee working in parallel, each agent brings a different mental model to every decision.
Zeno — clarity under uncertainty. Lattice — Munger's latticework of mental models. No single framework is sufficient. Not a retail product. Not a screener. A decision engine built for concentrated capital allocation.
Every investment gets multiple lenses — philosophy, forensic, macro, and behavioral — running in parallel.
Quality gates before valuation. Accounting forensics and promoter behavior checks screen out bad actors before a single rupee is considered.
31 of 55 agents have explicit India-specific edge — built around SEBI filings, MCA data, promoter patterns, and market microstructure unique to Indian equities.
Each agent is a specialized analytical unit with a defined thesis, tracking signals, and output format. Agents don't operate in isolation — they feed into synthesis layers that produce multi-dimensional views of any investment.
Every investment gets simultaneous analysis from philosophy lenses (Graham, Munger, Bakshi), forensic quality gates, macro cycle positioning, and behavioral pattern detection. No single model is sufficient.
Every agent produces classified signals — Direct (buy/sell), Filter (trust gates), Context (framework enrichment), Risk (avoidance warnings), and Infrastructure (data plumbing). Structured outputs, not noise.
When a filing drops, agents fire in parallel — earnings quality, management commentary, promoter behavior, macro backdrop. The Scenario Engine models outcomes while the Pessimist stress-tests the bull case.
30+ India sources — SEBI EDIFAR, MCA21, RBI bulletins, NSDL/CDSL bulk deal data, con-call transcripts, annual report parsing. 56% of all agents have explicit India-specific edge built into their architecture.
Agents are trained on curated repositories — Indian corporate fraud patterns (Satyam, DHFL, Harshad Mehta, Ketan Parekh, NSEL, Sahara, Unitech), historical failure signatures, regulatory enforcement archives, and alternative datasets that public models never see. This isn't generic intelligence repackaged. It's structured, domain-specific knowledge that compounds with every analysis cycle.
ZenoLattice is available by invitation. Tell us about yourself and we'll be in touch.