AI app for it and development · no coding needed
Source-linked retrieval answer console
Reduce time spent locating and verifying answers while keeping every response linked to its source.
Made for: IT and development teams answering questions from their own documents, databases and applications
What it does for you
The problem
Answers are scattered across documents, databases and applications, so teams cannot trace where a response came from or keep it current.
What it gives you
Reviewer-approved grounded answers with source references
What you give it
Permitted data sourcesuploaded private datasetsquery settings
Build your own version of Verta RAG System, Powerdrill and more
One app with what these 10 AI tools do, yours to keep and change: Verta RAG System, Powerdrill, Baselight AI, Vext, Superpowered AI, Tilores Identity RAG, Farspeak, Airweave, R2R, Super RAG.
Everything these tools do, in one app
- External data integration Connects to external data sources to enrich responses with relevant information.Found in Verta RAG System, Powerdrill, Baselight AI and 2 more
- Retrieval-augmented generation Combines document retrieval with language model generation to produce context-aware answers.Found in Verta RAG System, Tilores Identity RAG, Super RAG
- Private dataset upload Allows users to upload their own data to create tailored knowledge bases.Found in Powerdrill, Baselight AI
- No-code knowledge base creation Enables building AI-powered knowledge bases without writing code.Found in Powerdrill
- Traceable answers with sources Provides answers that include the underlying data, sources, and query logic for verification.Found in Baselight AI, R2R
- Structured data catalog Offers a large catalog of structured datasets accessible at query time.Found in Baselight AI
- SQL editing and visualization Provides a studio for SQL editing and visualizations to analyze data.Found in Baselight AI
- Customizable query handling Allows adjusting retrieval parameters and generation style to suit different needs.Found in Verta RAG System, Super RAG
- Real-time processing Delivers quick responses and real-time document retrieval for efficient task completion.Found in Verta RAG System, Superpowered AI, Super RAG
- User-friendly interface Offers an intuitive interface for managing and monitoring retrieval workflows.Found in Verta RAG System, Vext, Superpowered AI and 1 more
- Content generation Generates text such as articles, reports, and marketing materials.Found in Vext, Superpowered AI, Farspeak
- Data analysis tools Identifies patterns and generates insights from data.Found in Vext, Superpowered AI
- Customizable templates Provides templates that can be tailored to different industries and use cases.Found in Vext
- Workflow automation Automates routine tasks and workflows to improve productivity.Found in Superpowered AI
- Multi-language support Supports multiple languages and content formats for broader usability.Found in Superpowered AI, Farspeak
- API access Offers API access for integration with other applications and workflows.Found in Farspeak, R2R
- Semantic search across sources Performs semantic searches across various applications, databases, and document stores.Found in Airweave
- Data syncing options Supports manual, scheduled, and event-driven data syncing with version tracking.Found in Airweave
- Autonomous research Conducts autonomous research across local documents and online sources.Found in R2R
- Knowledge graph construction Builds knowledge graphs for structured information representation.Found in R2R
How it works, step by step
- Connect external data sources
- Retrieve documents and combine them with language model generation
- Upload private datasets
- Build knowledge bases without code
- Show answers with sources and query logic
- Query a structured data catalog
- Edit SQL and build visualizations
- Adjust retrieval parameters and generation style
- Process documents and answer in real time
- Manage and monitor retrieval workflows in one interface
- Generate text such as articles, reports and marketing materials
- Identify patterns and generate insights from data
- Apply customizable templates by industry and use case
- Automate routine tasks and workflows
- Support multiple languages and content formats
- Expose API access for other applications
- Run semantic search across applications, databases and document stores
- Sync data manually, on schedule or on events with version tracking
- Run autonomous research across local documents and online sources
- Build knowledge graphs for structured representation
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned reviewer-approved grounded answer set with source references and unresolved questions
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Source-linked retrieval answer console with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Source-linked retrieval answer console with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links5 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare24 KB
- prompt-vps.mdThe same build on your own server (Docker)24 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria12 KB
- demo/index.htmlThe working demo on sample data196 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
Reduce time spent locating and verifying answers while keeping every response linked to its source. For IT and development teams answering questions from their own documents, databases and applications, convert permitted data sources, uploaded private datasets and query settings into reviewer-approved grounded answers with source references. The benefit is a testable hypothesis, measured through accepted answers per reviewer hour and corrections after answer approval; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect permitted data sources, uploaded private datasets and query settings, then follow this sequence: 1. Connect external data sources. 2. Retrieve documents and combine them with language model generation. 3. Show answers with sources and query logic. Resolve uncertain cases with qualified reviewers, approve reviewer-approved grounded answers with source references, and measure accepted answers per reviewer hour and corrections after answer approval against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One fixed source set and permission scope; final factual and access checks remain human. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve source attribution, access permissions and data rights. Named owners approve substantive changes and external use. One fixed source set and permission scope; final factual and access checks remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.
What to build first
Pilot scope: One fixed source set and permission scope; final factual and access checks remain human. Implement one approved input format, a bounded representative case set and the first two task modules: connect external data sources; retrieve documents and combine them with language model generation. Support the third module with operator review: show answers with sources and query logic. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
What it can connect to
Customer-owned documents, databases and applications. Cloud storage, identity providers, ticketing and messaging destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Source connection and permissions, Retrieval and answer workspace, Review and delivery. Use a thumbnail gallery for knowledge bases, a large central answer canvas, and a right-hand panel for sources, retrieval settings and comments. Let users compare answer versions side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant source passage. Make the task-specific outcome reviewer-approved grounded answers with source references visible beside its evidence, review state and value baseline.
