スタートアップが提案する、より信頼性の高いAI回答の提供方法：チャットボットをクラウドソーシングする
Buyers Edge PlatformのCEO John Davieが、単一LLMの hallucination やデータ漏洩リスクを回避するため、複数の大規模言語モデルを統合して回答を融合するCollectivIQを創業し、エンタープライズ向けに提供を開始した。
キーポイント
複数LLMの統合と回答融合
ChatGPT、Gemini、Claudeなど最大10のモデルに同時にクエリを送り、結果を比較・融合させることで、単一モデルよりも精度の高い回答を実現する技術を採用している。
エンタープライズにおけるAI導入の課題
社内の従業員が外部のAIツールを使用することで社内情報が学習データ成为るリスクや、誤情報（hallucination）がビジネス資料に混入する問題に対処する必要があった。
セキュリティとコストモデル
プロンプトデータの暗号化を実施し、CollectivIQがAPIトークンコストを負担する一方、顧客は使用量に応じて課金されるという新しいビジネスモデルを構築した。
CollectivIQの資金調達状況
創業者のDavie氏が独自で資金を調達しており、年内に外部からの資本募集を検討している。
Davie氏の起業体験への思い
28年ぶりの新規立ち上げとなる今創業を楽しんでおり、開発現場に密着して製品構築に取り組んでいる。
プロンプトデータに関する訂正
記事の更新により、CollectivIQがすべてのプロンプトデータを削除しないことが明確になった。
影響分析・編集コメントを表示
影響分析
このニュースは、エンタープライズAI市場において「単一モデル至上主義」からの脱却と、「マルチモデル統合による品質担保」という新たなトレンドを示唆しています。企業はセキュリティと精度の両立を求めるため、複数のLLMをラッパーとして利用する中間層ソリューションへの需要が高まる可能性があります。ただし、この手法が計算コストの増大やレイテンシの問題をどう解決するかは今後の実証次第です。
編集コメント
複数のLLMを並列実行して回答を融合するアプローチは、ハルシネーション対策として注目されますが、その分、処理コストと応答速度への影響が無視できません。エンタープライズ用途では「精度」と「コスト/速度」のトレードオフをどう定義するかが、このビジネスモデルの成否を分ける鍵となります。
信頼性の高いAI回答を実現するスタートアップの手法：チャットボットのクラウドソーシング
CollectivIQは、ChatGPT、Gemini、Claude、Grok、および最大10種類の他のモデルから情報を統合した回答を同時に提示することで、ユーザーのAIクエリに対してより正確な回答を提供することを目指しています。
原文を表示
John Davie wanted Buyers Edge Platform, the hospitality procurement enterprise he founded and still leads, to benefit from the AI wave. When he looked around, the CEO wasn’t satisfied with the options.
The answer was CollectivIQ, a Boston-based company incubated at Buyers Edge Platform that gives users more accurate answers to their AI queries by showing them responses that pull information from ChatGPT, Gemini, Claude, Grok — and up to 10 other models — all at the same time.
When new AI tools began hitting the market a few years ago, Davie told TechCrunch he was excited about the potential and encouraged his employees to try them out. His optimism was short-lived.
“We had a bit of a wake-up call about a year ago when we learned that if our employees are just using any various AI tools, or even their own license, it could be training on our company information,” Davie said. “We could be essentially edging our competitor.”
Davie looked into more secure enterprise AI contracts and discovered expensive long-term contracts for large language models that produced inaccurate information and hallucinations.
“We hated having to decide which employees deserved AI,” he said. “What really made it worse, employees were complaining about hallucinated, biased answers. Sometimes it was really giving us flat, incorrect answers that made their way into PowerPoint presentations and cover presentations.”
He challenged his chief technology officer to build something better.
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The result was CollectivIQ. The spinout created a tool that queries several large language models, including those from OpenAI, Anthropic, Google, and xAI at the same time. The software searches for overlapping and differing information to produce a fused answer that is meant to be more accurate than those produced by each LLM on its own.
All the data involved with CollectivIQ prompts is encrypted.
“As somebody who just loves technology, you’re always looking for the best of the best, right?” Davie said. “You always want to have the latest, greatest iPhone or laptop or tool and I wanted to give my employees the best of the best of AI, but there was really nothing out there that you know would bring them all together into one.”
CollectivIQ started rolling the software out internally to its employees at the beginning of 2026. The initial response was strong, Davie said. Once Davie learned that many of Buyers Edge Platform’s customers were dealing with the same confusion or hesitation around adopting AI tools, the company decided to release it to the public.
The software was built using AI model enterprise APIs. CollectivIQ pays for the token costs and its customers pay by usage, which Davie hopes will help the company stand out in a crowded enterprise AI market.
“I’m hoping that this is a breath of fresh air for companies that see that they are not going to have to be committed,” Davie said. “They’re only going to pay for the value they get out of it.”
CollectivIQ was fully funded by Davie, who told TechCrunch he plans to seek outside capital at some point later this year. For Davie, it’s been fun to be back building a new startup nearly 28 years after he launched his current company.
“It does feel like way back in the day and we are doing it all over again and being scrappy and being very in the weeds on LLMs and post training and all sorts of things I was not trained in,” Davie said. “It’s fun and exciting. I go sit hand and hand with the software developers building the product, that’s how I got my main company, it’s a lot of fun.”
This piece has been updated to correct the fact that CollectivIQ does not delete all prompt data.
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Becca is a senior writer at TechCrunch that covers venture capital trends and startups. She previously covered the same beat for Forbes and the Venture Capital Journal.
You can contact or verify outreach from Becca by emailing rebecca.szkutak@techcrunch.com.
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