Knowledge-backed answers
Organize approved website content, documents, policies, service details, and FAQs so answers can be grounded in sources the business owns and reviews.
AI chatbot development in Savannah
Turn website conversations into useful next steps.
F09 Tech builds business chatbots that answer from approved information, qualify inquiries, collect the right context, connect to useful workflows, and hand customers to a person when judgment is needed.
- Customer support
- Lead qualification
- Knowledge retrieval
- Human handoff
Chatbot experience map
- 01Define the job and audience
- 02Organize approved knowledge
- 03Design conversations and actions
- 04Test, launch, and improve
Clear scope, useful answers, controlled actions, and accountable ownership
AI chatbot services
A chatbot designed around the conversation after hello.
A useful chatbot needs more than a model and a chat window. We design the knowledge, questions, actions, boundaries, handoffs, measurement, and ownership that turn a demo into a dependable business experience.
Lead and service conversations
Design questions that identify intent, collect relevant details, explain next steps, route requests, and avoid making promises the business cannot support.
Workflow connections
Connect validated conversations to approved actions such as scheduling, CRM records, support tickets, notifications, forms, or structured follow-up.
Boundaries and human handoff
Define sensitive topics, tool permissions, escalation conditions, privacy expectations, refusal behavior, logging, review, and transfer to a person.
How the engagement works
Design the service before choosing the model.
We begin with customer intent and the business outcome, then define approved knowledge, conversation paths, connected actions, risk controls, testing, and ongoing ownership.
- 01
Discover
Identify the audience, recurring questions, lead or support goals, existing content, systems, and handoff expectations.
- 02
Design
Define knowledge sources, conversation paths, required fields, response boundaries, actions, and human escalation.
- 03
Build
Configure retrieval, prompts, integrations, access controls, analytics, alerts, and the customer-facing experience.
- 04
Test
Evaluate common, ambiguous, sensitive, out-of-scope, and adversarial questions before exposing the chatbot to customers.
- 05
Improve
Review unresolved questions, failed handoffs, content gaps, conversion signals, and risk events on an agreed schedule.
What gets delivered
A chatbot with a job, a boundary, and an owner.
The implementation includes the operational documentation needed to maintain content, review conversations, manage integrations, and improve the experience after launch.
OWASP guidance on prompt injectionOWASP identifies direct and indirect prompt injection as important risks for language-model applications. We treat chatbot inputs as untrusted, limit access, test boundaries, and design human oversight around the use case.- Use-case, audience, success criteria, exclusions, and escalation definition
- Approved knowledge inventory, source ownership, update process, and content-gap list
- Conversation map, qualification fields, actions, handoff paths, and fallback responses
- Integration, permission, privacy, retention, logging, and alert configuration
- Functional, answer-quality, boundary, handoff, and adversarial test results
- Launch checklist, analytics baseline, review cadence, and improvement backlog
Good fit signals
A strong fit when visitors need answers before they become leads.
Chatbot development is most valuable when the business receives repeat questions, loses after-hours website inquiries, or needs a consistent way to collect context before a person follows up.
- Website visitors repeatedly ask the same service, availability, process, or qualification questions.
- Contact forms collect too little context, creating slow or unproductive follow-up.
- Useful answers are scattered across pages, documents, inboxes, and individual employees.
- The team needs a clear handoff from automated conversation to sales or support.
Common questions
Clear answers before you commit.
What can an AI chatbot do for my business?
A chatbot can answer common questions, explain services, collect lead details, qualify inquiries, guide customers to the right resource, schedule an approved next step, create a support request, and hand the conversation to a person with useful context.
What information does the chatbot use?
The approved source set can include website pages, service documents, policies, FAQs, product information, and selected internal knowledge. We define which sources are authoritative, who owns updates, and what the chatbot should not answer.
How do you reduce incorrect AI answers?
The design narrows the chatbot's purpose, grounds answers in approved sources, adds response boundaries, limits tool access, tests realistic and adversarial questions, and creates clear human handoff paths. AI output still requires ongoing review and improvement.
Can the chatbot connect to our CRM or scheduling tools?
Yes, when the platform provides a suitable integration or API. A scoped workflow can pass validated lead details, create records, check approved availability, schedule appointments, open tickets, or notify the right team without exposing unnecessary access.
Will customers be able to reach a real person?
Yes. Human handoff should be designed from the beginning. The chatbot can offer contact options, route high-value or sensitive conversations, collect context before transfer, and clearly explain when a person will follow up.
Give your website a more useful first conversation.
Start with the questions customers ask, the details your team needs, and the point where a person should take over. We will map the smallest valuable chatbot and its safest path to launch.