--- title: "Knowledge Agents: Cited Answers From Your Data | AppStream Studio" description: "Knowledge agents retrieve, ground, cite, and synthesize answers across your enterprise data, respecting existing permissions. Engineered and operated by AppStream." url: https://appstream.studio/solutions/agents/knowledge-agents markdown_url: https://appstream.studio/solutions/agents/knowledge-agents.md --- 1. [Solutions](https://appstream.studio/solutions.md) 2. [Engineer](https://appstream.studio/solutions/engineer.md) 3. Agent types 4. Knowledge Agents Knowledge Agents # Answers from your own knowledge, with the source attached. Your team has the information, spread across wikis, drives, tickets, and warehouses. They can’t find it fast enough, or trust it when they do. Knowledge agents retrieve, ground, cite, and synthesize across all of it. We engineer them, and we run them in production. [Talk to an AI engineer](https://appstream.studio/schedule-a-discovery-call.md) · [Explore Engineer](https://appstream.studio/solutions/engineer.md) [Part of 02 Engineer Turn possibility into production. Data & knowledge engineering](https://appstream.studio/solutions/engineer.md) Where this sits in the lifecycle 1. [01 Advise](https://appstream.studio/solutions/advise.md) 2. [02 Engineer You are here](https://appstream.studio/solutions/engineer.md) 3. [03 Operate](https://appstream.studio/solutions/operate.md) [Govern Runs across all three](https://appstream.studio/solutions/govern.md) The frontier capability behind it ## Agents are the mechanism. The capability is the point. - ### Reasoning systems Models work through policy, rules, and edge cases, and show how they reached the answer. Where it lands Eligibility, underwriting, compliance review - ### Multimodal AI Documents, images, and forms become structured data without anyone keying them in. Where it lands Invoices, medical records, field photos The problem ## The problem isn’t a lack of data. It’s finding and trusting it. Wikis go stale, shared drives become graveyards, and generic AI fills the gaps with confident guesses. - Knowledge spread across five or more systems searched separately - Generic AI tools that invent answers to domain questions - Stale documents nobody knows not to trust - Compliance and legal needing every answer cited How we work ## Four steps. One team the whole way. 1. 01 ### Map the knowledge Audit where answers live, what to ground the agent in, and what to keep out. 2. 02 ### Design retrieval Chunking, embeddings, hybrid search, and reranking tuned to how your people actually ask. 3. 03 ### Engineer it in Wired into your identity, your data, and your audit log, with citations from day one. 4. 04 ### Govern and tune Watch what’s asked, what’s cited, and what’s drifting, and keep the corpus current. What’s included ## What knowledge agents covers. In practice. - ### Hybrid retrieval Vector search, keywords, and reranking, tuned to what works on your data. - ### Citation-first design Every answer comes with its source, so it can be checked. - ### Permission-aware Your existing access controls apply to what the agent can read. - ### Multi-source synthesis One question answered across wiki, SharePoint, Salesforce, and the warehouse at once. - ### Freshness tracking Stale documents are flagged, and low-confidence answers go to a person. - ### Domain tuning Retrieval and prompts tuned to your vocabulary, not generic web language. What you can hold us to ## Commitments. Not marketing ranges. What every build commits to. Performance is measured on your own work during the engagement, not quoted from industry ranges. every answer Cited Links, pages, and passages back to the source aware Permission People only retrieve from documents they can already see when it doesn’t know Says so Low-confidence questions route to a subject expert Go deeper ## Other kinds of work agents take on. - [Engineer Turn possibility into production. Build the applications, agents, integrations, and data infrastructure that put AI inside real business workflows.](https://appstream.studio/solutions/engineer.md) - [Workflow Agents Take the manual workflow off your team, step by step.](https://appstream.studio/solutions/agents/workflow-agents.md) - [Customer-Facing Agents Resolve the request, not just reply to it.](https://appstream.studio/solutions/agents/customer-facing-agents.md) - [Multi-Agent Systems For the process that crosses systems, teams, and decision rights.](https://appstream.studio/solutions/agents/multi-agent-systems.md) - [Agent operations Once it’s live, someone has to own it. How we run agents in production and keep them improving.](https://appstream.studio/solutions/agent-operations.md) ## Bring us your documentation. We’ll make it answer. Wherever the answers actually live: wikis, PDFs, ticket history, someone’s head. We’ll show you what it takes to get cited answers out of it. [Talk to an AI engineer](https://appstream.studio/schedule-a-discovery-call.md) · [See our work](https://appstream.studio/case-studies.md) --- ## AppStream Studio AppStream turns frontier AI capabilities into production systems that perform real work. Talk to an AI engineer: https://appstream.studio/schedule-a-discovery-call · Email: contact@appstream.studio - [Home](https://appstream.studio/index.md) - [Solutions](https://appstream.studio/solutions.md) - [Advise](https://appstream.studio/solutions/advise.md) - [Engineer](https://appstream.studio/solutions/engineer.md) - [Operate](https://appstream.studio/solutions/operate.md) - [Govern](https://appstream.studio/solutions/govern.md) - [How we work](https://appstream.studio/how-we-work.md) - [Work (case studies)](https://appstream.studio/case-studies.md) - [Industries](https://appstream.studio/industries.md) - [Insights](https://appstream.studio/blog.md) - [Partners](https://appstream.studio/partners.md) - [About](https://appstream.studio/about-us.md) - [Contact](https://appstream.studio/contact.md)