theCloaq Earns a 55 Proof of Usefulness Score by Building an Intelligence Workspace that Unifies Scattered Knowledge

Welcome to the Proof of Usefulness Hackathon spotlight , curated by HackerNoon’s editors to showcase noteworthy tech solutions to real-world problems. Whether you’re a solopreneur, part of an early-stage startup, or a developer building something that truly matters, the Proof of Usefulness Hackathon is your chance to test your product’s utility, get featured on HackerNoon, and compete for $150k+ in prizes. Submit your project to get started ! In this interview, we speak with Oluwatunmise Olatunbosun to discuss theCloaq , an AI-powered workspace and support platform. We delve into how the platform connects fragmented workflows, automates ticket management, and provides source-attributed answers to streamline operations for engineering and customer support teams. What does theCloaq do? And why is now the time for it to exist? theCloaq is an intelligence workspace and support platform that connects scattered knowledge (docs, wikis, tickets, Slack, email) and turns them into source-attributed answers via hybrid retrieval, embeddings, and reranking. It runs real support workflows, ingests and classifies tickets, detects SLA breaches and incident patterns, surfaces prior runbooks, drafts replies, and powers automations across tools with background workers keeping integrations, vectors, and alerts continuously synced. Now’s a good time for theCloaq to exist because… What is your traction to date? How many people does theCloaq reach? As we are pre-launch and are in active testing, it reaches 20 organizations currently. Who does theCloaq serve? What’s exciting about your users and customers? theCloaq is built for Customer support teams and engineering organizations that operate across fragmented tooling that lose time searching across tickets, docs, wikis, slack, emails, and conversations for answers that already exist. It is most useful for teams with repeated incidents, SLA pressure, scattered knowledge, and high support volume. What technologies were used in the making of theCloaq? And why did you choose ones most essential to your techstack? theCloaq is built on a highly performant and modern stack, leveraging Bun, TypeScript, PostgreSQL, TimescaleDB, and Redis for speed and robust data management. To handle complex knowledge graphs and advanced search, the team utilizes Neo4j, Storyblok, Weaviate, Qdrant, OpenAI embeddings, and a custom gRPC reranker service. Everything is seamlessly orchestrated using n8n for automations, RabbitMQ for messaging, and Docker for deployment. What is traction to date for theCloaq? Around the web, who’s been noticing? theCloaq recently concluded its private beta tests and is preparing for a scheduled public launch on July 17, 2026. The team is currently building momentum through direct B2B outreach and social media marketing, projecting an initial milestone of onboarding over 50 support teams within the first 30 days of going live. theCloaq scored a 55 proof of usefulness score ( https://proofofusefulness.com/report/thecloaq ) - how do you feel about that? Needs reassessed or just right? 55 is honest. It reflects a working product in active testing, not yet in wide production use. The scoring criteria reward real-world adoption metrics (active users, retention, revenue), and those numbers will shift significantly after July 17th. Ask us again in 90 days. What excites you about theCloaq's potential usefulness? * What excites the most is the gap it bridges. Teams repeatedly solve the same incidents and support issues because the answer is buried across tools. By combining ticket history, documentation, customer conversations, runbooks, incident signals, and automation into one searchable intelligence layer. We help reduce response time, improve sla performance, and help teams resolve future problems with evidence from past work. Walk us through your most concrete evidence of usefulness. Not vanity metrics or projections - what's the one data point that proves people genuinely need what you've built? The runbook extraction pipeline is the clearest proof. When a ticket closes, theCloaq analyzes the full conversation and tries to extract a structured runbook. It doesn't save everything the system only keeps extractions that pass a quality threshold, and it runs duplicate checks to avoid building up noise. The proof isn't the extraction itself. It's what happened before Cloaq existed. Runbooks worth of institutional knowledge were sitting in closed tickets, completely invisible to every agent who ran into the same problem later. Once extracted and indexed, those became the first result the next time a similar ticket came in. What confirmed genuine need: beta organizations didn't connect integrations and leave. They kept them synced and queried. The answers they got back weren't generic. It was grounded in their own team's actual past work, with the source attached. That's a different thing from a chatbot, and teams felt the difference. How do you measure genuine user adoption versus "tourists" who sign up but never return? What's your retention story? The signal we track is retrieval query frequency, not logins but active searches against integrated knowledge sources. A team that connects an integration and never queries it is a tourist. A team running 20+ queries a week against their ticket history and Notion docs is genuinely adopted. We also track integration sync counts, runbook-to-ticket conversion rate, and whether workflow automations are being triggered, not just configured. If we re-score your project in 12 months, which criterion will show the biggest improvement, and what are you doing right now to make that happen? User adoption and retention. The platform compounds every ticket that closes, generating a potential runbook. Every integrated source makes future queries more accurate. The teams that stick through the first two weeks see that compounding kick in and don't leave. Right now we're focused on shortening the time to first value, i.e., getting an org's first integration synced, their first meaningful query answered, and their first runbook surfaced within the first session. That's the activation moment that drives everything downstream. How Did You Hear About HackerNoon? Share With Us About Your Experience With HackerNoon. I've been reading HackerNoon for years. Stumbled across the Proof of Usefulness hackathon and figured it was a good reason to finally write something. Since theCloaq has been tested by 20 organizations in private beta, what specific feedback or SLA metric from those initial pilot organizations gives you the most confidence going into your July 2026 launch? Honestly, the feedback we kept hearing was simple, We wish we had this sooner. Teams were tired of digging. That was enough for us. You mentioned a goal of onboarding 50+ support teams in your first 30 days. How do you plan to scale your direct B2B outreach and marketing to hit that aggressive growth target so quickly? We're not doing anything fancy. We're reaching out directly to support teams, leaning on our beta users to spread the word, and showing up in the right communities. The Product Hunt launch helps too. 50 teams in 30 days is ambitious but it keeps us focused. With the platform heavily relying on hybrid retrieval and embeddings to unify fragmented tools, how do you ensure the generated answers remain accurate and avoid hallucinations during high-pressure incidents? We have a base threshold, i.e no relevant source, no answer. The system only responds with what it can actually point to. If it can't find something relevant, it tells you that instead. Meet our sponsors Bright Data: Bright Data is the leading web data infrastructure company, empowering over 20,000 organizations with ethical, scalable access to real-time public web information. From startups to industry leaders, we deliver the datasets that fuel AI innovation and real-world impact. Ready to unlock the web? Learn more at brightdata.com . Neo4j: GraphRAG combines retrieval-augmented generation with graph-native context, allowing LLMs to reason over structured relationships instead of just documents. With Neo4j, you can build GraphRAG pipelines that connect your data and surface clearer insights. Learn more . Storyblok: Storyblok is a headless CMS built for developers who want clean architecture and full control. Structure your content once, connect it anywhere, and keep your front end truly independent. API-first. AI-ready. Framework-agnostic. Future-proof. Start for free . Algolia: Algolia provides a managed retrieval layer that lets developers quickly build web search and intelligent AI agents. Learn more .