Build a conversational assistant that helps people find information or complete a defined task. Code Huddle develops custom AI chatbots for websites, software products, and internal teams. We agree what the assistant should answer, which systems it can access, and when a person should take over before choosing the implementation.
Capability map
A chatbot is a conversation interface; its usefulness depends on the information and workflows behind it. Start with the audience, the questions they ask, and what a successful conversation should achieve. Huddle Chat Bot demonstrates our work on knowledge ingestion, chatbot configuration, and website embedding. Dine Talk demonstrates voice and web ordering workflows. These are product examples, not promises of accuracy, adoption, or delivery time for your project. A custom build is useful when your access rules, integrations, or user journey need more than a configurable product provides.
Review representative questions, existing support material, and the task users need to complete. Compare a configured chatbot product with custom development. Define supported topics, answer boundaries, escalation rules, and the acceptance criteria for a useful first release.
Connect selected documents, help content, or permitted records through retrieval. Preserve source references where appropriate, decide how content is refreshed, and test incomplete or conflicting information. The assistant should acknowledge missing evidence instead of inventing an answer.
Design the chat interface around your product, including mobile layouts, keyboard access, conversation states, and authentication where needed. Scope an embedded widget, an in-app assistant, or an API integration according to the users and channels you actually need.
Connect approved systems for tasks such as checking a record, preparing a support request, or collecting structured information. Validate inputs and enforce access in the application. Require confirmation for agreed changes and keep a clear distinction between a proposed action and a completed one.
Define what happens when the assistant cannot help, an integration is unavailable, or the user asks for a person. Agree the destination and information shared at handoff. Handle timeouts and interrupted conversations, and make any support-hours or response expectations clear to users.
Test representative questions, unsupported requests, stale sources, and attempts to access restricted information. Review answer support, task completion, response time, and operating cost. Keep an evaluation set for changes to content, prompts, models, and connected systems after launch.
Bring the information you already have. We use it to agree a useful first scope, identify dependencies, and explain what the estimate includes.
Content readiness, channels, authentication, integrations, evaluation, and handoff requirements shape the build estimate. Text, voice, model, retrieval, storage, and hosting usage have different recurring costs. The proposal records the assumptions and separates implementation from ongoing operation.
Review whether a configured product meets the task before commissioning a custom build. For a custom project, agree the conversation scope, review an integrated assistant against sample questions, and release after the agreed answer and handoff checks. Voice and additional channels are scoped separately.
Delivery model
Review users, sample questions, content readiness, access rules, and existing systems. Compare product configuration with a custom build and agree the first release scope.
Build the interface, retrieval, and approved integrations. Review real conversations and test missing information, restricted records, handoff, and provider failures against the acceptance criteria.
Release to the agreed audience, monitor quality and cost, and hand over the configuration and evaluation set. Assign owners for source updates, incident handling, and future changes.
Commercial model
Defined outcomes can use milestones. Evolving products are usually better served by transparent team capacity. Estimates follow discovery of workflows, integrations, constraints, and acceptance criteria.
Engineering judgment
Build versus buy, delivery speed, operating cost, security, maintainability, migration, and technical ambition are discussed as product decisions—not hidden implementation details.
Where this fits
Technology choices
The final stack follows product constraints, team capability, integration boundaries, security, scale, and long-term ownership.
Explore product stories with related architecture, workflows, and delivery decisions.
See how clients describe the communication, engineering, and delivery on their software projects. Each review refers to its own engagement.
Read client feedbackQuestions before starting
Practical questions and scope decisions before you commission a build.
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