Beginner
No code. Done in <30 min.
Intermediate
Some Python. 1–3 hrs.
Advanced
Full-stack. Production-ready.
No Code
UI only. Any skill level.
BeginnerNo Code

FAQ Chatbot in 5 Minutes

Turn a plain-English description of your business into a working chatbot using Claude Projects. Zero setup — share via link with your team.

Claude.ai No Code Any Business
5 min  ·  Claude.ai View Example →
No CodeBusiness

AI Agent in Microsoft Teams

Deploy an agent inside Microsoft Teams using Copilot Studio. Connect to Outlook Calendar and email. No developer needed — done through a visual UI.

Copilot Studio Microsoft Teams M365
1 hr  ·  Copilot Studio View Example →
Intermediate

Insurance Annuity Advisor Agent

A full intake agent that asks qualifying questions, recommends the right annuity product, books advisor calls in Outlook, and emails a summary — all automatically.

Claude API Python Outlook Insurance
2–3 hrs  ·  Python View Example →
Intermediate

Lead Qualification Agent

Watches a Gmail inbox for inbound leads, scores them with GPT-4 against your ideal customer profile, routes qualified leads to Slack, and logs everything to a spreadsheet.

Python Gmail API Slack Sales
3 hrs  ·  Python View Example →
Intermediate

Claims Intake (FNOL) Agent

First Notice of Loss agent — collects incident details via chat, validates coverage against policy rules, classifies claim type, and routes to the right adjuster via email.

Claude API Python Insurance
3 hrs  ·  Python View Example →
No CodeBeginner

HR Onboarding Assistant

Guides new hires through their first weeks: introduces team members, schedules intro meetings, answers policy questions, and collects completed forms — all via Teams chat.

Copilot Studio Teams HR
1 hr  ·  Copilot Studio View Example →
Intermediate

Sales Outreach Agent

Reads a lead list from Google Sheets, researches each prospect via web search, drafts personalized emails, routes senior contacts to Slack for approval, then sends and logs results.

Claude API Google Sheets Slack Sales
2 hrs  ·  Python View Example →
Advanced

Web Chat Widget

Deploy your agent as a chat bubble on any website. Flask backend + Claude API + plain HTML/JS frontend. Customers chat from their browser — no app, no login required.

Python / Flask Claude API HTML / JS
Half day  ·  Python + HTML View in Insurance Example →
Intermediate

Document Q&A Agent (RAG)

Upload your policy documents, compliance manuals, or product guides. Ask questions in plain English and get accurate answers with source citations — no hallucinations.

Claude API LlamaIndex Python
2 hrs  ·  Python View Example →
Intermediate

Customer Service Triage Agent

Reads incoming support tickets, classifies them by urgency and topic, routes to the right team, drafts a suggested response, and logs to a CRM — reducing triage time by 80%.

Claude API Email CRM
2–3 hrs  ·  Python View Example →
Intermediate

Policy Renewal Outreach Agent

Monitors a spreadsheet of renewal dates, sends personalized email outreach 30/14/7 days before expiry, tracks responses, and escalates non-responders to a rep.

Python Outlook API Insurance
2 hrs  ·  Python View Example →
BeginnerNo Code

Meeting Summarizer & Action Item Extractor

Paste a meeting transcript into Claude. Get a structured summary, decision list, action items with owners, and a follow-up email draft — in under 30 seconds.

Claude.ai No Code Productivity
2 min  ·  Claude.ai View Example →
Intermediate

Patient Intake & Triage Agent

Collects symptom data via secure chat, triages urgency using clinical criteria, routes critical cases to on-call staff immediately, and pre-fills EHR intake forms for routine appointments.

Claude APIPythonHealthcare
3–4 hrs  ·  Python View Example →
Intermediate

Contract Review & Risk Flagging Agent

Upload NDAs, MSAs, or vendor contracts. The agent extracts key terms, flags non-standard clauses, compares against your template, and outputs a redline summary with risk scores.

Claude APILlamaIndexLegal
2–3 hrs  ·  Python View Example →
Advanced

Financial Report Analysis Agent

Ingests earnings reports, 10-Ks, and analyst transcripts. Extracts KPIs, benchmarks vs. prior period, runs sentiment analysis on management commentary, and generates a one-page investment memo.

Claude APIPythonFinance
Half day  ·  Python Coming Soon
No CodeBeginner

Personal Assistant Agent with n8n

Monitors your Gmail and calendar. Every morning: summarizes unread emails, flags urgent items, lists today's meetings, and sends a Slack digest. Built entirely in n8n's visual canvas.

n8nGmailSlackNo Code
2 hrs  ·  n8n View Showcase →
Beginner · No Code · 5 min
Example 1: FAQ Chatbot in 5 Minutes
Use Claude Projects to create a working chatbot with zero setup. Works for any business — just describe it in plain English.
  1. 1

    Go to claude.ai and create a Project

    Open claude.ai → click ProjectsNew Project. Name it after your use case (e.g. "Product FAQ Bot").

  2. 2

    Add instructions in plain English

    Click Project Instructions and describe your agent. Example:

Example instructions (edit for your business)
You are a helpful assistant for [Your Company Name].
Your job is to answer questions from customers or employees.

Topics you can help with:
- [Topic 1, e.g. product features, pricing, policies]
- [Topic 2, e.g. how to submit a claim, renewal process]
- [Topic 3]

Keep answers short and friendly — 2-4 sentences.
If you don't know something, say: "Great question — let me connect you with the right person."
Never make up information. Only answer based on what you know above.
  1. 3

    Test it — then share

    Start a new chat inside the project and test it with real questions. Click Share to give your team a link. That's it — your agent is live.

Pro tip: Add an "Upload file" to the Project with your product documentation, policy PDF, or FAQ document. Claude will answer questions based on its contents — no extra setup needed.

No Code · 1 hr · Copilot Studio
Example 2: AI Agent in Microsoft Teams
Build a fully connected agent inside Teams — no developer required. Connects to Outlook Calendar and Email through Copilot Studio's visual UI.
  1. 1

    Open Copilot Studio

    Go to copilotstudio.microsoft.com — already included in your Microsoft 365 plan.

  2. 2

    Create an Agent

    Click Create → New Agent. Describe your agent in plain English. Copilot Studio generates the structure automatically.

  3. 3

    Connect to Outlook (optional)

    Go to Actions → Add an action → Office 365 Outlook. Select Create event for calendar or Send an email. No code — just map the fields.

  4. 4

    Deploy to Teams

    Go to Channels → Microsoft Teams → Turn on Teams → Publish. Your agent appears in Teams within minutes.

  5. 5

    Share with your team

    In Teams, search for your agent's name in Apps, or share the direct link Copilot Studio generates. Pin it to the Teams sidebar for easy access.

Want Claude instead of GPT? In Agent Settings → Model, select Claude Sonnet. You get Claude's reasoning quality with Teams deployment — best of both worlds.

No-Code Showcases
Step-by-step walkthroughs using n8n, Dify, and Copilot Studio — see agents work without writing a line of code.
n8n — Personal Email & Calendar Assistant
No Code · Beginner · ~2 hours
  1. 1

    Install n8n (free)

    Go to n8n.io and use the cloud trial, or run it locally with npx n8n. No credit card needed for the cloud trial.

  2. 2

    Create a new workflow

    Click New Workflow. Add a Schedule Trigger node set to run every morning at 7am.

  3. 3

    Connect Gmail

    Add a Gmail nodeGet Messages. Set filter: unread, last 24 hours. Connect your Google account via OAuth — n8n walks you through it.

  4. 4

    Add Claude to summarize

    Add an Anthropic nodeMessage model. Set the prompt: "Summarize these emails in bullet points. Flag anything urgent or time-sensitive." Pass the Gmail output as context.

  5. 5

    Send to Slack

    Add a Slack nodeSend Message. Target your personal DM or a #daily-digest channel. Pass the Claude summary as the message body. Save and activate.

Extend it: Add a Google Calendar node before Claude to include today's meetings in the summary. Add a second Claude call to draft replies for the 3 most urgent emails.

Dify — RAG Chatbot in 30 Minutes

Upload your company docs to Dify's knowledge base. Connect to Claude or GPT. Publish as a web widget. Your team can ask questions and get accurate, cited answers in real time — no hallucinations.

Dify Docs →

Dify — Multi-Step Research Agent

Use Dify's workflow canvas to build: web search → extract key points → fact-check with a second LLM call → format report → send to email. All visual, no code, ~1 hour to build.

Open Dify →

MindOS — Personal AI Brain

MindOS lets you create a persistent AI that knows your context: projects, contacts, goals, preferences. Ask it to draft based on past context, manage your to-dos, or research on your behalf.

Try MindOS →
Use-Case Library by Industry
Real deployments and patterns, organized by sector. Laymen read the use case; developers download the boilerplate.
Healthcare
Intermediate
Patient intake & triage — Agents collect symptoms, triage urgency, and route to the right care team. Clinical documentation — ambient AI agents transcribe patient-doctor conversations and auto-fill EHR fields (used by Nuance DAX). Medication adherence — proactive reminder agents via SMS/WhatsApp with escalation paths.
IBM Healthcare AI → Boilerplate: Coming Soon
Legal
Intermediate
Contract review — Agents scan NDAs, MSAs, and vendor contracts for non-standard clauses, flagging risk and comparing vs. playbook. Due diligence — ingest 100s of documents and surface key risks in hours, not weeks. Legal research — cite-accurate answers to case law queries using RAG over legal databases.
Harvey.ai Case Study → Boilerplate: Coming Soon
Finance
Advanced
Earnings analysis — Agents parse 10-Ks, extract KPIs, and generate analyst memos. Fraud detection escalation — agents that analyze transaction patterns, flag anomalies, and route to human reviewers with context. Client portfolio summaries — daily automated briefs for advisors with personalized client insights.
JPMorgan AI → Boilerplate: Coming Soon
Insurance
Intermediate
Claims FNOL — Agents collect incident details, validate coverage, and route to adjusters automatically. Underwriting intake — process submissions, extract risk factors from documents, and pre-score applications. Policy renewal outreach — 30/14/7-day automated sequences with personalized policy summaries.
See Full Example →
Sales & Marketing
Beginner
Lead qualification — Agents score inbound leads against ICP, route qualified ones to Slack, and log to CRM. Personalized outreach — research prospect LinkedIn + web presence, draft a tailored email, require human approval before sending. Competitive monitoring — daily agents that track competitor pricing/product changes and alert the sales team.
n8n AI Examples → Boilerplate: Coming Soon
HR & People Ops
Beginner
Onboarding assistant — Guides new hires through their first week via Teams: intros, policy Q&A, form collection, and meeting scheduling. Benefits navigator — answers employee questions about benefits, PTO policy, and open enrollment. Performance review aid — helps managers draft structured feedback from notes using consistent rubrics.
Boilerplate: Coming Soon
Responsible AI Deployment Checklist
Vet whether an autonomous agent is safe to deploy. 12 questions every business should answer before going live.
  • 1
    Human-in-the-Loop defined?

    Have you identified every irreversible action the agent can take (send email, move money, delete data) and added a human approval step for each?

    Safety
  • 2
    Least-privilege access enforced?

    Does the agent only have access to the systems and data it needs for its specific task — nothing more?

    Governance
  • 3
    Audit trail implemented?

    Is every action the agent takes logged with a timestamp, input, output, and rationale — queryable by your compliance team?

    Governance
  • 4
    Kill switch in place?

    Can you disable the agent in under 60 seconds without needing a developer? Is there a clear escalation path for unexpected behavior?

    Safety
  • 5
    Data privacy reviewed (GDPR / AIA)?

    Does the agent process personal data? If yes, is there a DPIA completed? Do you have a lawful basis for processing under GDPR? Is the model hosted in a compliant region?

    Privacy
  • 6
    EU AI Act risk tier assessed?

    If you operate in or serve EU customers: have you determined whether this agent is high-risk (healthcare, HR, finance, law enforcement) under the EU AI Act? High-risk systems require conformity assessments.

    Governance
  • 7
    Prompt injection hardened?

    Has the agent been tested against prompt injection attacks — where malicious content in external documents tries to override the agent's instructions?

    Safety
  • 8
    Hallucination guardrails in place?

    For any agent that generates factual outputs (summaries, recommendations, reports): is there a verification step (RAG grounding, citations, human review) before that output is acted on?

    Safety
  • 9
    Users informed?

    Are customers or employees interacting with this agent aware they're talking to an AI? Transparency is legally required in some jurisdictions and best practice everywhere.

    Governance
  • 10
    Bias & fairness tested?

    For agents that make decisions affecting people (hiring, lending, healthcare triage): has the agent been tested for discriminatory outputs across demographic groups?

    Governance
  • 11
    Production monitoring active?

    Is someone (or a system) watching for unexpected behavior, cost spikes, error rates, and latency regressions after launch? Who gets paged at 2am if the agent goes rogue?

    Ops
  • 12
    Rollback plan documented?

    If the agent causes an incident, can you revert to the previous state? Is there a documented incident response plan that includes AI-specific failure modes?

    Ops

Score yourself: 12/12 = production-ready. 8–11 = address gaps before launch. Below 8 = high risk — don't deploy yet. This checklist is a starting point; regulated industries (healthcare, finance, legal) require additional domain-specific compliance steps.