Building a Financial AI That Can Show Its Work
Inside Ask Linc’s architecture: provider normalization, semantic data packs, deterministic calculators, canonical facts, provenance, validation, and evidence-backed financial reasoning.
How Ask Linc Works
Show the Math: How Ask Linc Makes AI Financial Analysis Transparent
See how Ask Linc keeps the numbers, assumptions, calculations, checks, and sources attached to every financial answer so you can verify the work.
Why Determinism Matters in AI Financial Analysis
LLMs are non-deterministic by design. Discover how Ask Linc separates AI reasoning from fixed calculations to ensure consistent, reproducible financial results.
Why We Switched to Claude and Gemini
Why Ask Linc moved from a single AI model to Claude for reasoning and Gemini for structured data — and the measurable difference it made for users.
Inside the Ask Linc Financial Reasoning Pipeline
A layer-by-layer breakdown of how Ask Linc separates LLM reasoning from deterministic calculations to deliver accurate, hallucination-free financial analysis.
How We Built a Model-Routing Architecture for Financial AI
See how Ask Linc routes queries between Claude and Gemini using a deterministic calculation engine — a technical deep-dive into our multi-model AI architecture.
Why AI Apps Should Stop Using a Single Model
See why routing each AI query to the right model can improve accuracy, reliability, and cost compared with a brittle single-model architecture.