# How to research your competitors with AI in one morning > Guide to AI competitor research: noise-free search with Kagi, sourced answers with Oso.ai and cross-model synthesis with YesChat, in one morning. - Canonical: https://serchai.com/en/guides/ai-competitor-research/ - Site: Serchai (https://serchai.com) — AI tools comparator - Language: en - Updated: 2026-07-25 --- ## Tools you will use - [Kagi](https://serchai.com/en/reviews/kagi/) — The paid search engine with no ads and no tracking. - [Oso.ai](https://serchai.com/en/reviews/oso-ai/) — An AI search engine that answers and summarizes instead of listing links. - [YesChat](https://serchai.com/en/reviews/yeschat/) — GPT, Claude, Gemini and video generators under a single subscription. ## The steps, in short 1. **Define what you need to know and from whom** — List your three to five real competitors and the concrete questions that will decide something in your business. 2. **Find what their websites do not say with Kagi** — Use lenses and domain controls to surface real reviews, complaints and mentions outside the official story. 3. **Interrogate each source with Oso.ai** — Turn each competitor's public documentation into answers with cited sources. 4. **Synthesize the comparison with YesChat** — Cross-check the material with two different models and produce the decision document. > **TLDR:** Researching competitors with AI is not asking a chatbot what it thinks of your rival: it is using each tool for what it does. Kagi finds what competitors do not tell (complaints, forums, real reviews), Oso.ai answers with cited sources over their public documentation, and YesChat cross-checks the material with two models to produce the final comparison. One morning of work, starting from $0. This guide is for people who make positioning, pricing or product decisions by looking at the market: founders, marketing leads, product folks. Classic competitor research dies in one of two ways: an expensive report that expires in three months, or twenty open tabs that never become anything. The flow's principle: chatbots hallucinate company data fluently, so no claim enters the final document without a source. The tools speed up search and synthesis, and the cited source is the quality control. ## 1. Define what you need to know and from whom Research without concrete questions produces folders of screenshots nobody reopens. Before touching any tool, two lists. First: your three to five real competitors, the ones appearing in the same sales conversations as you, not the sector's twenty. Second: the questions whose answers would change one of your decisions, along the lines of what their entry price is, what their homepage promises, what their customers complain about or what they have shipped this year. Each question must pass the so-what filter: if the answer does not feed a pricing, messaging or product decision, off the list. With this, the research morning has a map and a criterion for when to stop. ## 2. Find what their websites do not say with Kagi Your competitor's website tells their version. Useful research starts where their story ends: customer reviews, forum threads, user comparisons, job postings that reveal where they are heading. For that search, [Kagi](/en/reviews/kagi/) has two levers free search engines lack: lenses to filter by forums and communities when you want real complaints, and domain controls to bury the press-release aggregators that pollute any brand search. Search each competitor's name next to friction words (cancel, alternative, problem, pricing) and save every finding with its URL. From $5 a month with a free trial, and for a morning like this it pays for itself. Its full review is on the site, and its direct counterpart in this flow appears in the next step. ## 3. Interrogate each source with Oso.ai With sources located, it is extraction time. [Oso.ai](/en/reviews/oso-ai/) is conversational search with sources cited in every answer: ask about a competitor's pricing model or their free plan's limits, and it returns the answer linking where each claim comes from. That link is the difference between researching and believing things: every data point gets verified with one click before entering your document. Keep one conversation per competitor: follow-up questions (and how much is that per year, and what happens past the limit) go deeper without repeating context. It has a free plan and starts at $8 a month. Answers without a clear source get marked pending, not written down as facts. ## 4. Synthesize the comparison with YesChat The material from steps 2 and 3 is a pile of notes with URLs. Synthesis turns it into a one-page document per decision: a compared pricing table, a message map (what each one promises on their homepage) and the gaps list, what nobody in the market is saying. [YesChat](/en/reviews/yeschat/) lets you run that synthesis with a safety net: paste your notes and ask GPT and Claude for the analysis separately. Where both models agree, the reading is probably solid. Where they diverge, there is a nuance to check by hand, and those divergences are often the most interesting part of the exercise. Free plan enough for the method, paid from $8 a month. The final document feeds the rest of your marketing directly: message gaps become angles for the [sales deck](/en/guides/ai-sales-deck/) and topics for the [newsletter](/en/guides/ai-newsletter/). Every task in the sector is in [AI for marketing and social media](/en/ai-for/marketing/), and the rest of the category's tools in the [best AI productivity tools](/en/best-ai/productivity/) ranking. ## Common mistakes Asking the chatbot about your competitor directly. Models mix stale data, confuse similar companies and invent prices with total confidence. Without a cited source there is no data, there is rumor. Researching twenty competitors. Breadth kills depth and the morning becomes a week. Three to five real rivals researched properly decide more than a sector census. Confusing their marketing with their reality. A competitor's homepage is their aspiration. Their negative reviews, support threads and job postings are their reality. Both layers matter, but they do not mix. Researching without an expiry date. A year-old pricing comparison misinforms more than having nothing. Date the document and repeat the exercise quarterly: with the flow in place, the refresh takes an hour. ## Frequently asked questions ### How much does this flow cost? Starting: nothing, since Oso.ai and YesChat have free plans and Kagi offers a trial. The paid set lands at around $21 a month, and if you only research quarterly, the free tiers plus Kagi's trial cover each round. ### Can I not do all this with a single chatbot? You can do it worse. A generalist chatbot does not surface the forum complaints Kagi filters for, nor does it cite sources with Oso.ai's discipline. The result's reliability comes from the division of roles, not from prompt volume. ### How often should the research be repeated? Quarterly for pricing and messaging, which move the most, and always before a big decision: a price change, a repositioning, a launch. With the step 1 questions saved, every repeat is incremental. ### Is it legal to research competitors this way? Everything this flow uses is public information: websites, reviews, forums and open documentation. Nothing private is accessed. The line not to cross is posing as a customer to extract non-public terms, and this method does not need it.