About Frank by Chrisputer Labs
Product research sucks. You Google something, get ten SEO-optimized listicles that all recommend the same Amazon bestsellers, and walk away knowing less than when you started.
Frank is not a person. Frank is a set of AI models that read real reviews and write an honest comparison, and says so when the evidence is too thin to trust. When you ask a question here, Frank doesn't just check one source. He reads Reddit discussions, forum posts, independent reviews, and manufacturer specs, then works through it all for a brutally honest analysis. One ranking, not two hundred reviews.
What makes this different
- +Real sources. We pull from actual user discussions and reviews, not just manufacturer claims.
- +No sponsored picks. We don't get paid to recommend products. Affiliate links exist, but they never influence rankings.
- +Honest cons. Every product has drawbacks. We tell you what they are instead of burying them.
- +Shareable results. Every report gets a permanent link you can bookmark or share.
How the research works
Every report from Frank is written by AI, not a human editor. Every time you submit a query, Frank runs a multi-stage pipeline. A planning model decomposes your question into sub-queries. A request for "best budget mesh wifi" expands into separate searches for coverage, throughput, ease of setup, price, and common failure modes. Those sub-queries fan out across search engines, Reddit threads, manufacturer spec sheets, and review-site feeds.
The raw sources get scored and deduplicated. An agent loop takes notes as it reads, so the final write-up has a grounded paper trail instead of a pile of fragments. A separate writing model turns that paper trail into the report, prompted to surface cons, call out marketing fluff, and skip products it can't verify. "We honestly don't have enough data" is a valid answer here, and you'll see it occasionally. That's intentional. The full breakdown, including which models do which step, lives on the how it works page.
Results get cached so you don't pay for a re-run. If someone asked the same question (or a canonically equivalent one) in the last 14 days, you get that existing report, with a "Re-research with fresh data" button in case you want a fresh run anyway.
What we don't do
We don't fabricate product data. If the sources don't support a claim, it doesn't end up in the report. We don't rank products by commission rate. We don't republish manufacturer press releases as reviews. We keep thin, product-less pages out of discovery, because they hurt everyone.
Affiliate disclosure
Frank contains Amazon Associates and other affiliate links. When you buy a product through one of our links, we may earn a small commission at no extra cost to you. This helps keep the site running. Affiliate relationships never influence our product rankings or recommendations. The product that wins is the product the reviews say wins.
The deployed worker is intentionally zero-dependency: zero runtime npm dependencies, no runtime node_modules, and zero third-party tracking scripts. A dev-only test harness exists for local testing, but every runtime line is hand-written and auditable — a deliberate stance against supply-chain risk.