Historical Withdrawal Rate Analysis for Smarter Retirement Planning
Go beyond the 4% rule. Ask Linc calculates your personalized withdrawal rate using real historical market data, giving you a range of outcomes — not just one number.
Ethan Teng
Why Perplexity × Plaid Signals a Shift from Financial Dashboards to Financial Conversations
Perplexity's expanded Plaid integration points to a broader trend: intelligent finance, where AI answers questions grounded in your actual accounts and the broader market. Here's how Ask Linc is built for that shift.
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.
Stress Testing Your Retirement Portfolio Using Historical Market Data
See how Ask Linc stress-tests your retirement plan across historical market crashes, inflation shocks, and sequence-of-returns risk.
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.
From Macro Context to Personal Insights: A New Layer of Portfolio Intelligence
Ask Linc combines live market data with your actual brokerage holdings to deliver personalized portfolio analysis, stress testing, and retirement projections.
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.