Platform Architecture
One deterministic engine.
Three professional deployments.
Every SigmaCore product is built on the same principle: the LLM reasons and narrates, the deterministic engine computes and verifies. This architectural separation is what eliminates hallucinations by design — not by prompt engineering, but by ensuring LLMs never perform tasks requiring numerical or factual precision.
Product 1
Eliza — SigmaCore FP
Financial planning conversations for startups
Product 2
Lex — SigmaCore Legal
Citation verification for legal briefs
Product 3
Azile — SigmaCore FinVerify
MCP server + document verification
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LLM Reasoning Layer — Claude / GPT / Gemini
Interprets context · Captures assumptions · Generates narrative · Never performs calculations
SigmaCore Core Engine — Patent Pending
Python / Decimal Deterministic Computation & Verification
200+ verified financial functions · Legal database API · PostgreSQL audit trail · Exact decimal arithmetic · Full auditability at every step · Schema-validated inputs · Reproducible outputs
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Verified, auditable, deterministic outputs
FP Output
Hallucination-free financial models · P&L · cash flow · KPIs
Lex Output
Verified citations · Good law status · Rule 11 certificate
Azile Output
Verified computation results · Document accuracy audit
◆ Why This Architecture Matters
LLMs generate text probabilistically — the same prompt can produce different numerical results across runs. Financial projections, legal citations, and audit computations all require deterministic precision: the same inputs must always produce the same outputs. SigmaCore's architecture enforces this by design. No competitor currently enforces this separation at the system level.