AI app for it and development · no coding needed
Source-linked embedded assistant console
Own one assistant stack instead of renting several subscriptions.
Made for: Product teams embedding AI chat assistants into their own apps and websites
What it does for you
The problem
Assistant features are rented across several tools, so prompts, memory, guardrails and analytics sit in separate places the team does not own.
What it gives you
Source-linked assistant and administrator console
What you give it
Model keysknowledge sourcesguardrail ruleschannel settings
Build your own version of OpenAI Assistants API, AI Agent Platform by CometChat and more
One app with what these 10 AI tools do, yours to keep and change: OpenAI Assistants API, AI Agent Platform by CometChat, Conva.AI, AI Assistant and Bot Builder, ChatbotGPT, AnswerFlow AI, Mistral Agents API, Secton Platform, Conversation API, Agent M - Powered by Floatbot.AI.
Everything these tools do, in one app
- Natural language understanding Understands and generates human-like responses to user queries.Found in OpenAI Assistants API, ChatbotGPT, Agent M - Powered by Floatbot.AI
- Multi-turn conversations Maintains context across multiple back-and-forth messages.Found in OpenAI Assistants API, ChatbotGPT
- Customizable assistant behavior Lets you adjust how the assistant responds via settings.Found in OpenAI Assistants API, ChatbotGPT, Conva.AI
- Embeddable chat UI Provides a ready-made chat interface to embed in apps or sites.Found in AI Agent Platform by CometChat, AI Assistant and Bot Builder
- Agent builder A tool to create and configure user-facing AI agents.Found in AI Agent Platform by CometChat, Conva.AI, AI Assistant and Bot Builder
- Connect external agents Allows linking third-party AI agents to the platform.Found in AI Agent Platform by CometChat
- Safety guardrails Restricts assistant responses to safe, relevant topics.Found in AI Agent Platform by CometChat, Conva.AI
- Human handoff Escalates conversations to a human when needed.Found in AI Agent Platform by CometChat
- Analytics and notifications Monitors usage and sends alerts about interactions.Found in AI Agent Platform by CometChat, Agent M - Powered by Floatbot.AI
- Multi-model support Lets you choose from different AI models like OpenAI, Azure, or Claude.Found in AI Assistant and Bot Builder
- Database integrations Connects to databases and tools like Firebase, Notion, or Google Sheets.Found in AI Assistant and Bot Builder
- No-code interface Enables building assistants without writing code.Found in AI Assistant and Bot Builder
- Prebuilt templates Offers ready-made assistant setups for common use cases.Found in AI Assistant and Bot Builder
- Persistent memory Keeps conversation context across sessions.Found in Mistral Agents API, Conversation API
- Tool connectors Integrates with tools for code execution, web search, and image generation.Found in Mistral Agents API, Conversation API
- Multi-agent orchestration Coordinates multiple AI agents to solve complex tasks.Found in Mistral Agents API
- API-first integration Provides an API for developers to add AI features easily.Found in Secton Platform, OpenAI Assistants API, Mistral Agents API and 1 more
- Automatic state management Handles conversation storage and state without extra infrastructure.Found in Conversation API
- Versioned prompts Keeps live conversations stable when prompts or configs change.Found in Conversation API
- Multi-channel deployment Deploys the assistant across websites, messaging apps, and social media.Found in Agent M - Powered by Floatbot.AI
- Customizable conversation flows Allows tailoring the conversation path to business needs.Found in Agent M - Powered by Floatbot.AI
How it works, step by step
- Understand natural language queries and generate replies
- Maintain context across multi-turn conversations
- Adjust assistant behavior through settings
- Embed a ready-made chat UI in apps or sites
- Build and configure user-facing agents
- Connect external third-party agents
- Apply safety guardrails to restrict topics
- Escalate conversations to a human when needed
- Monitor usage and send interaction alerts
- Choose among supported AI models
- Connect databases and tools such as Firebase, Notion or Google Sheets
- Build assistants without writing code
- Start from prebuilt assistant templates
- Keep conversation context across sessions
- Connect tools for code execution, web search and image generation
- Coordinate multiple agents on complex tasks
- Expose an API for developer integration
- Manage conversation state without extra infrastructure
- Keep live conversations stable with versioned prompts
- Deploy across websites, messaging apps and social media
- Tailor conversation flows to business needs
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned source-linked assistant and administrator console 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 embedded assistant 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 embedded assistant 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 criteria11 KB
- demo/index.htmlThe working demo on sample data195 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
Own one assistant stack instead of renting several subscriptions. For product teams embedding AI chat assistants into their own apps and websites, convert model keys, knowledge sources, guardrail rules and channel settings into a source-linked assistant and administrator console. The benefit is a testable hypothesis, measured through accepted assistant replies per support hour and corrections after deployment; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect model keys, knowledge sources, guardrail rules and channel settings, then follow this sequence: 1. Understand natural language queries and generate replies. 2. Maintain context across multi-turn conversations. 3. Adjust assistant behavior through settings. Resolve uncertain cases with qualified reviewers, approve source-linked assistant and administrator console, and measure accepted assistant replies per support hour and corrections after deployment 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 model set and one embed target; final tone, safety and escalation checks remain human. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve user privacy, source attribution, reply accuracy and usage permissions. Buyers approve substantive changes and deployment scope. One fixed model set and one embed target; final tone, safety and escalation 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 model set and one embed target; final tone, safety and escalation checks remain human. Implement one approved input format, a bounded representative case set and the first two task modules: understand natural language queries and generate replies; maintain context across multi-turn conversations. Support the third module with operator review: adjust assistant behavior through settings. 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 model keys, knowledge bases and permitted data sources. Cloud asset storage, app and website embed targets 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: Assistant builder and sources, Editable conversation preview, Admin console and analytics. Use a thumbnail gallery for assistants, a large central builder canvas, and a right-hand panel for sources, guardrails and comments. Let users compare prompt versions side by side. Display draft, changes requested and approved states. Provide an embed preview link with comments anchored to the relevant reply. Make the task-specific outcome source-linked assistant and administrator console visible beside its evidence, review state and value baseline.
