經過驗證的機會，而不是摘要
Perplexity 和 ChatGPT 回傳的是需要你自行解讀的研究摘要。Iris 最後給出的是聚焦且明確的機會建議：哪個利基市場、為什麼是現在、下一步該怎麼做。
Iris·Deep ResearcherAI Research Agent that turns insights into products
Iris reads the market, the audience, and the SERPs, then hands a structured brief to your AI Team so research turns into a product.
Research that ends in a shipped product, not a PDF.
受到這些公司的創作者信賴：
Why research never reaches the codebase
Reports that die in Notion
Perplexity gives you an answer. SparkToro gives you a chart. Both end as a doc somebody pastes into Notion and nobody reads in week 3. Iris hands her findings to Emma so research becomes a PRD.
Single-source answers you cannot trust
One LLM summary or one trend chart is not a market read. Iris synthesizes search, communities, audience data, and competitor pages into one cited view you can interrogate, not just accept.
Trends that look real but are not
Exploding Topics shows a chart trending up. It does not tell you whether the demand is durable or a TikTok blip. Iris validates trends across signals before you commit a sprint to building for them.
Three weeks from question to decision
Discovery, interviews, competitor scans, slide deck, exec review. By the time the deck lands the founder already picked a direction. Iris compresses the loop into one Editor report your team can challenge the same day.
與Iris的一天
從你的第一個提示詞到交付成果——這就是 Iris 的實際運作方式。
- 01
傾聽你的想法或問題
Iris 將「我該做 X 嗎？」轉化為可研究的假設——該驗證什麼，該忽略什麼。
- 02
跨多個來源深度搜尋
搜尋引擎、論壇、市集、應用程式商店、社群平台——比單一一次 Google 搜尋更廣泛。
- 03
梳理需求和競爭訊號
規模、成長、意圖、付費意願、現有玩家——全部整理成可比較的訊號圖譜。
- 04
按可行或不可行對利基領域排序
為機會評分，讓你看到的是「這個利基、這個切入角度、這些證據」，而不是一堆研究資料。
- 05
Everything Iris needs for trustworthy research
Multi-source data synthesis
Combines search results, community signals, audience data, and competitor pages into one structured view.
Cited findings
Every key claim is backed by a source link so you can verify the evidence yourself.
Underserved need detection
Identifies recurring user complaints and feature gaps competitors are not addressing.
Competitor weakness mapping
Maps where existing players are weak so you know where to position.
Audience segmentation
Breaks the market into segments with distinct needs instead of one monolithic user.
Structured Editor reports
Findings land in an Editor block with sections, takeaways, and recommendations.
Direct handoff to PM
Conclusions feed straight into Emma so research turns into PRD inputs, not a dead document.
當Iris加入你的團隊後，會發生什麼變化
手動打造的工作流程緩慢、仰賴人工且工具繁雜。將滑鼠懸停在任一卡片上，查看為何每項提升都很重要。
為什麼創作者會在眾多選擇中選Iris
對比
正從 ChatGPT Deep Research 轉來？以下就是 Iris 更勝一籌的地方。
能轉化為產品的研究
獨立的研究工具只會回傳一份 Google 文件。Iris 會把經過驗證的利基市場交給 Emma，由她撰寫規格說明；接著 Alex 建構產品。你的洞察會在同一次會話中轉化為已交付的軟體。
為建造者而生，而非分析師
大多數深度研究工具優化的是引用與廣度。Iris 優化的是 go-or-no-go 決策：「這個市場是真的嗎？有什麼證據支持？在這裡能勝出的最小產品是什麼？」
Atoms 與 Perplexity Pro：比較功能、價格和能力
| 功能 | Atoms 推薦 | Perplexity Pro |
|---|---|---|
| 輸出 | 已驗證的機會 | 研究摘要 |
| 直接交接為產品規格 | 直接傳送給 Emma | 你把它複製到文件裡 |
| 結合訊號評分的利基排名 | 內建於 | 僅敘述 |
| 同一工作階段內啟動產品 | 是 | 僅研究 |
| 來源廣度 | 多來源，含論壇、交易市集 | 網頁 + 輕量論壇 |
Iris 如何與您的其他 AI 團隊成員協作
Iris 並不是單獨工作。以下是你與完整團隊協作建置時，各項交接如何落地。
What Iris researches for builders
Concrete research questions Iris answers with evidence and a path to product.
- Scan a market
Market opportunity scans
Find underserved niches in a market before committing to building anything.
- Dive on a competitor
Competitor deep dives
Map competitor positioning, weaknesses, and pricing patterns in one report.
- Profile an audience
Audience persona research
Understand who the users are, where they hang out, and what they actually complain about.
- Validate a trend
Trend validation
Test whether a trend is real and durable before building on it.
- Benchmark pricing
Pricing benchmark
See how competitors price, package, and bundle so your pricing decision has a baseline.
- Run discovery
Pre-PRD discovery
Run the discovery work before writing a PRD so Emma builds on real insight, not assumption.
Try these prompts with Iris
Scan a market for underserved niches
@Iris find underserved niches in the personal finance app market for Gen Z in the US. Pull from search, Reddit, and the top 10 incumbents. Identify 3 gaps with evidence and hand the top one to Emma to scope.
Deep dive a single competitor
@Iris deep dive Notion. Map their pricing, positioning, recent product moves, community sentiment, and where their power users are leaking. Cite every claim and flag the two weaknesses we could exploit.
Validate a trend before we build
@Iris is "AI agent for accountants" a real durable trend or a 6-month hype cycle? Check search velocity, community discussions, funding signals, and incumbent moves. Tell me if it is worth Emma writing a PRD for.
Profile an audience before launch
@Iris profile freelance designers earning $80k-$200k/year in the US. Where do they hang out, what tools do they hate, what do they complain about? Hand the persona to Emma so the PRD reflects real users, not assumptions.
認識 Iris 的其他 AI 團隊成員
沒有任何一個智能體是單獨工作的。點選任一隊友，即可查看他們如何處理您產品中的那一部分。
常見問題
Put Iris to work
Stop researching in one tool and building in another. Let Iris run discovery and hand her findings to your AI Team in Atoms.
