AI Chatbot Development Deliverables Checklist: What to Include in Your Project Brief

Hiring an AI chatbot developer? This checklist covers the key deliverables you should include in your project brief: conversation flow diagrams, NLP training data, integration code, testing reports, and deployment documentation. Use this list to set clear acceptance criteria, avoid scope creep, and ensure you get a working chatbot that meets your business goals. Whether you need a customer support bot or a lead gen assistant, these deliverables apply across platforms like Fiverr.

Many buyers hire an AI chatbot developer without a clear deliverables checklist, leading to missed expectations, endless revisions, and a bot that doesn't actually solve user problems. Common mistakes: skipping conversation flow design, not defining fallback behavior, forgetting to specify integration requirements (e.g., CRM, WhatsApp), and failing to agree on testing criteria. Without a checklist, you might receive code that works in a sandbox but fails under real traffic, or a bot that can't handle typos or off-script questions. This guide helps you avoid those pitfalls by listing exactly what to ask for.

When posting a job for an AI chatbot developer, your project brief should specify these deliverables. Use this checklist to define acceptance criteria upfront.

- A visual map (e.g., flowchart or decision tree) showing all user paths, intents, and bot responses.

- Must include: welcome message, main menu, common questions, fallback handling, and escalation to human agent.

- Acceptance: The diagram should cover at least 80% of expected user queries.

- A list of intents (e.g., "cancel order", "track shipment") with at least 10-15 training phrases per intent.

- Entities extracted (e.g., order number, date).

- Acceptance: The bot correctly identifies intents with >90% accuracy on a test set you provide.

- State machine or script that handles context, slot filling, and multi-turn conversations.

- Example: If user says "I want to return a shirt", the bot asks for order number and reason.

- Acceptance: All defined flows complete without errors.

- Code or configuration for connecting to your backend (CRM, database, messaging platforms like Slack or WhatsApp).

- Must include authentication, error handling, and logging.

- Acceptance: Integration works end-to-end with your test environment.

- A document showing test cases, results, and bug fixes.

- Tests should cover: happy path, edge cases (typos, empty input), and load testing (if applicable).

- Acceptance: No critical bugs; response time under 2 seconds for 95% of queries.

- Step-by-step guide to deploy the bot on your server or cloud (AWS, Google Cloud, etc.).

- Includes environment variables, dependencies, and monitoring setup.

- Acceptance: You can deploy the bot independently following the docs.

- All code delivered via GitHub or zip, with clear comments and a README.

- Acceptance: Code is linted, modular, and follows best practices.

- Agree on a support period (e.g., 2 weeks) for bug fixes and minor tweaks.

- Acceptance: Developer responds within 24 hours during support period.

- Copy the list into your project brief on Fiverr.

- Ask the freelancer to confirm each deliverable before starting.

- Use the acceptance criteria to sign off on milestones.

This checklist works for any AI chatbot platform: Dialogflow, Rasa, Botpress, or custom LLM-based bots.

- No portfolio with live chatbots (screenshots of a flow are not enough).

- Vague about NLP training: if they can't explain how they handle out-of-scope queries, move on.

- Refuses to provide a testing report or demo.

- Overpromises: "Your bot will answer everything perfectly" — no bot is 100% accurate.

- "What platform do you recommend for my use case and why?"

- "How do you handle fallback when the bot doesn't understand?"

- "Can you show me a conversation flow diagram from a past project?"

- "What is your process for training intents? Do you use real user data?"

- "How do you ensure data privacy (GDPR, CCPA)?"

- Communication: Do they ask clarifying questions about your business?

- Technical depth: Can they explain how they handle context and entities?

- Portfolio quality: Look for bots that handle complex, multi-turn conversations.

- Testing approach: Do they have a systematic QA process?

- A cheap bot ($500-$1,500) may use a simple rule-based approach with limited NLP.

- Mid-range ($2,000-$5,000) typically includes proper intent training and integrations.

- Enterprise-grade ($5,000+) includes custom LLM integration, advanced analytics, and ongoing support.

- Timelines: Simple bot 1-2 weeks; complex bot 4-8 weeks.

Rough price ranges for AI chatbot development:

- Basic rule-based bot: $500–$1,500 USD, 1–2 weeks.

- Mid-range with NLP and integrations: $2,000–$5,000 USD, 3–6 weeks.

- Advanced LLM-powered bot with custom training: $5,000–$15,000+ USD, 6–12 weeks.

Cost drivers: number of intents (10 vs 50+), complexity of integrations (CRM, payment gateway), platform choice (Dialogflow vs custom LLM), and whether you need ongoing support. Always get a fixed-price quote with clear milestones.

The conversation flow diagram is the foundation. Without a clear map of user paths, the bot will feel disjointed. Ensure the developer provides this before coding starts.

At least 10–15 per intent for decent accuracy. For critical intents (e.g., 'cancel order'), aim for 20–30. The developer should also suggest adding more based on real user data after launch.

Yes, always. Specify in the contract that you own the full source code and can deploy it independently. Most freelancers on Fiverr agree to this.

Request a staging environment or a demo link. Run through all defined flows, test edge cases (typos, slang), and check response times. Use the testing report as a sign-off requirement.

That's normal for new bots. The developer should include a fallback mechanism (e.g., 'I didn't understand, can you rephrase?') and a plan for continuous learning using real user interactions.