Launching today
Owlish
Reduce support volume with AI agents trained on your docs
73 followers
Reduce support volume with AI agents trained on your docs
73 followers
Owlish turns your website, FAQs, docs, and PDFs into an AI customer support agent that answers common questions, cites sources, uses approved replies, and hands off to a human when needed. It helps businesses reduce repetitive support volume, reply faster outside business hours, and give support teams the context they need to resolve harder conversations.
Owlish
This looks soli. Citing the sources used for the answers is a huge trust builder for customers who might otherwise be skeptical of AI chat replies. How fast does Owlish update its answers if a business modifies an existing FAQ or policy document on their site?
Owlish
Thanks @vikramp7470, that’s exactly the problem we’re trying to solve: an answer is only useful if you can see where it came from.
For website/FAQ sources, Owlish doesn’t need a model retrain or redeploy. We re-crawl the source, replace the indexed chunks, and the agent uses the updated content on the next customer message after that sync finishes.
At launch, freshness is schedule-based rather than instant webhooks: weekly auto-sync is available on Scale, monthly on Growth, and teams can also trigger a manual sync when they need to refresh a source sooner. Once a sync starts, a changed page usually updates in minutes, depending on the size of the site and how much content changed.
Interesting positioning.
Have you noticed businesses being more concerned about hallucinations or about losing their brand voice/personality in AI support interactions?
Owlish
Hi, @surabhi_minocha!
Small sample size so far, but in the conversations I’ve had, accuracy tends to come up before brand voice.
A wrong answer about refunds, pricing, shipping, or policy can create a real support problem, so buyers want to know: “Will this make something up?” That’s why Owlish puts so much emphasis on source-grounded answers, citations, refusal, and human handoff.
Brand voice is the next layer. In the Agent Playground, teams can tune the agent’s instructions, personality, and system prompt until it sounds like their support team. And for high-stakes or recurring questions where they want exact wording, Direct Response feature lets them pin a specific answer the agent should use.
So the goal is both: accurate answers first, then answers that still feel like the business wrote them. Accuracy should never get sacrificed for personality.
The 'Direct Response' pinning feature is the most interesting design choice here. It lets businesses own the exact wording on high-stakes questions without losing the AI's ability to handle everything else. Curious what happens when a pinned response conflicts with a newer doc update. Does the pin always win?
Owlish
Hi, @dhiraj_patel5! For the specific question it matches, yes, the Direct Response is treated as the canonical answer.
That is intentional. If a business pins wording for something high-stakes like refunds, cancellation, pricing, medical disclaimers, legal language, etc., I don’t want a later website crawl to silently reinterpret it.
The nuance is that the pin does not override the whole knowledge base globally. It only applies when the customer’s question matches that Direct Response. If the policy changes, the business should update or remove the pinned answer too. Direct Responses are editable in place, so that is the fastest update path.
Longer term, I’d like Owlish to surface potential conflicts, like “your pinned refund answer no longer matches your refund page,” because that is exactly the kind of drift teams should not have to discover from a customer complaint.
super!! is it possible to use the knowledge base built by the platform to be used in Vapi?
Owlish
Thank you, @ashishkingdom! Not as a one-click connector today, but yes, this is technically possible.
The clean version would be a Vapi custom knowledge base integration: Vapi sends a search request during the call, Owlish searches the business’s Owlish knowledge base, then returns the relevant snippets or a pinned Direct Response for Vapi to speak.
Today, the practical path is to keep the same source material in sync across both systems. Owlish already has API/MCP surfaces for knowledge-base management, and a Vapi adapter is the kind of integration I’d like to support if enough voice-agent teams want it.
The source citation and human handoff parts are important here. AI support is useful, but customers need to know where an answer came from and when a real person should step in.
Owlish
Exactly, @farrukh_butt1! AI support should not feel like a black box.
The citation shows the customer and the support team where the answer came from. And handoff matters because some conversations should not be automated all the way through, especially when the customer is frustrated, the question is sensitive, or the agent does not have enough confidence.
The goal with Owlish is not to remove people from support. It is to let AI handle the repeatable questions, while making it clear when a human should step in.
Owlish
Hi, @lakshminath_dondeti!
Mintlify is primarily a documentation platform: publish and maintain docs, API references, and knowledge bases, with AI search/assistant features on top.
Owlish is more of a customer-support agent layer. It takes the knowledge a business already has — website, help docs, PDFs, FAQs — and uses it to answer customers in a web widget or support channels, cite sources, and hand off to a human when it shouldn’t guess.
So if a company’s docs are hosted on Mintlify, Owlish could treat those docs as a knowledge source. We’re not trying to replace the docs site itself.