Answer-engine products: when the answer is the product, margin is the moat
If your product is answering questions, your COGS is the model bill and your UX is the latency. The cache moves both — which makes it strategy, not plumbing.
For answer-engine products — vertical search, research assistants, Q&A over specialized corpora — the LLM call isn't a feature's cost, it's the cost of goods sold. Every margin point and every latency percentile is competitive surface. The companies that win this category will be the ones whose repeated answers cost nothing to serve.
Query convergence is the category's gravity: within any vertical, users orbit the same canonical questions with personal phrasing. Crowkis converts that gravity into unit economics — the popular head serves from cache at near-zero marginal cost, while spend concentrates on the novel tail where your product actually differentiates.
Reuse only when meaning, structure, confidence, and trust all agree.
Quality control is built into the serving path rather than bolted on: confidence gates keep uncertain matches away from users, freshness keeps time-sensitive verticals honest, and Enterprise Live Edit lets your team correct a cached answer in place the moment quality review flags it — with the change audited.
The bottom line
Watch the dashboard's economics shift as the corpus warms: cost per answered question falls week over week while p50 latency collapses. That curve is your pitch deck's favorite slide, and it compounds while you sleep.