0.x. Validate on staging first, keep your queue and provider setup healthy, and launch with confidence.
Setup docs
Built for Laravel teams running Filament
Filament Agentic Chatbot gives you source-grounded bots, visual workflow orchestration, embeddable delivery, Telegram and Slack channels, API endpoints, analytics, and rollout operations in one coherent package.
What ships today
Start with grounded answers, layer workflows where needed, and keep production visibility in one control surface.
Set up dedicated bots for support, sales, onboarding, and internal operations while each one keeps separate prompts, models, retrieval settings, and domain allowlists.
Replace "single-prompt hope" with explicit branching logic, validations, and audit-ready action paths across support and pre-sales journeys.
The same bot config runs in Filament, public pages, and authenticated surfaces using one setup and one source of truth.
Use one assistant brain for website widgets, Telegram, Slack, and service-to-service integrations without duplicate prompt logic.
Move from demo to production with setup checks, trace logs, queue visibility, and privacy controls already built into the operational loop.
Control where, when, and how assistants answer with signed embeds, domain allowlists, URL safety checks, and privacy-first defaults.
Workflow evidence
This showcase is backed by seeded workflows, plugin records, and real widget settings instead of AI stock graphics.
The demo assistant routes each visitor path into the right workflow: submission QA, image generation, fit check, pricing guidance, and structured feedback capture.
The same pattern scales in real projects: explicit intent routing, source-aware answers, channel-safe handoffs, and testable branches that can be published only after they pass rollout checks.
Realistic expectations
The honest pitch is stronger: you can ship useful assistants today, but you still own the rollout, sources, queues, and authorization model.
It accelerates assistant delivery, but it does not replace your product stack.
Buyer evaluation
The price is easiest to justify when you see how much admin UI, workflow runtime, widget delivery, channel plumbing, and operational tooling you do not have to build yourself.
Use the live widget and demo panel to test source-backed answers, citations, ingestion status, and knowledge gaps before you put an assistant in front of customers.
Evaluate lead qualification, support triage, implementation readiness, feedback capture, API handoffs, and workflow releases instead of judging the plugin by a generic chat prompt.
Check Bot Access Tokens, signed embeds, domain allowlists, budgets, channel diagnostics, queue requirements, usage analytics, privacy endpoints, and trace controls as part of rollout planning.
FAQ
These are the details that usually decide whether an embeddable AI chat widget stays a demo or becomes a maintained product surface.
It adds a production-minded control plane inside Filament: bot lifecycle, source ingestion, retrieval policy, workflow orchestration, access tokens, channel adapters, trace tooling, and analytics. You get the assistant as an actual product surface, not just a chat box.
No. The widget is one surface among many. The same bot setup can be shared across the Filament panel, external channels, and backend API access, so you avoid maintaining a separate stack for each touchpoint.
Yes. Start with a single grounded bot, connect a reliable source set, and tune retrieval and citations first. Add workflows later where user journeys need branching, data capture, or action calls.
They turn prompt behavior into a controlled graph with branch points, validations, API actions, and handoff logic. You can test every path, inspect traces, publish release versions, and roll back when a route starts to fail.
PHP 8.3+, Laravel 12+, Filament 5.2+, a queue worker, an AI provider, and vector storage for RAG. PostgreSQL with pgvector is the recommended base; ChromaDB can work in smaller setups.
Yes. You can place it on pages, documentation, help centers, or authenticated Laravel areas. In production, pair signed embed tokens, allowlists, rate controls, and queue-backed processing with your privacy policy.
Yes. Bot Access Tokens and connectors let you expose the same assistant through API integrations, Slack, and Telegram. The runtime keeps one conversation model and one operational surface for diagnostics.
You still own source quality, tenancy model, auth decisions, source refresh process, provider keys, billing, and incident response. The package helps you ship faster, but you still run the app and validate production rollout in staging.
Try the demo panel, review the architecture, and compare this control plane against the time it takes to build each channel yourself.
