AI chatbots and AI assistants handle the repeat conversations
An AI chatbot reads a message written in everyday language, works out what the person is asking, and replies or takes an action. AI assistants do the same job for your own staff, answering from your documents and systems. The assistant is set up so that requests outside its scope go to your team, with the conversation attached.
- Natural language understanding: people type the way they talk, and the assistant works out the intent.
- Context-aware conversations: it keeps track of what was said earlier in the chat, so a follow-up question does not start over.
- Multi-channel deployment: the same assistant can serve the channels people already use, such as website chat or a messaging app.
- CRM and API integrations: it can look up a record, create a ticket or update a contact.
Workflows that suit customer support automation and a knowledge assistant
Good candidates follow a pattern and draw on information you already have written down. These are common starting points.
- Customer service: answer order, account and policy questions from approved content, and pass unusual cases to a person.
- Internal helpdesk: handle routine IT and HR requests, and open a helpdesk ticket when a person needs to step in.
- Sales qualification: ask website visitors your sales team's questions, record the answers in your CRM, and offer qualified leads a calendar slot.
- Knowledge retrieval: a knowledge assistant searches your manuals, policies and past tickets, then answers with a reference to the source.
- Request intake: collect the details for a booking, quote or return and route them to the right team.
Beagle designs, builds and deploys the assistant in stages
Every engagement starts with a free 15-minute discovery call. We map your current operations, including how conversations reach you today, and identify the automation opportunities worth tackling first. You leave with a prioritized list of AI use cases. There is no pitch.
Solution design takes 1 to 2 weeks and produces a modular implementation plan. Data flows, integration points, KPIs and success criteria are defined before any code is written, with sign-off at every stage. For a chatbot, that typically means deciding which questions it answers, which content it draws on and when it hands over to a person.
Build and deploy takes 2 to 6 weeks, in iterative sprints. Each workflow goes through QA before production, and Beagle handles infrastructure, security configuration and staff onboarding. The final stage, optimize and evolve, is ongoing.
You own the assistant and its data, on an open, self-hosted stack
The assistant runs on an open, self-hosted stack: n8n for workflows, open-source AI models and Supabase for data. You keep full data ownership, with no vendor lock-in and no black boxes. If required, the solution can be deployed inside your own cloud environment.
The architecture is modular. Adding a voice agent, a new integration or more automations later does not require starting over.
Success is measured against KPIs agreed before the build
KPIs and success criteria are defined during solution design, before code is written. For customer support automation, candidates include how many conversations the assistant completes without a handover and how long people wait for a first reply. The measures that apply to your project are agreed with you at sign-off.
After launch, workflows are monitored against those agreed KPIs. Changes are based on real usage data, such as questions the assistant could not answer.
Start with a 15-minute call or a 2-minute assessment
Book the free 15-minute discovery call to talk through where AI chatbots or AI assistants fit in your operation. Or take the free AI readiness assessment: 5 questions, about 2 minutes, no sign-up, with an instant score and diagnostics.
You can also request the free AI Implementation Guide. It is personalized and emailed to you, and includes three quick wins for the next 30 days and a 90-day roadmap.
Questions buyers ask
Do we need in-house AI engineers to run a chatbot?
No. Beagle acts as your AI team, covering strategy, build, deployment and ongoing support. We involve your IT team for access and permissions, but you do not need in-house AI experts.
Where does our conversation data live?
Beagle builds on an open, self-hosted stack that uses Supabase for data. You keep full data ownership, and the solution can be deployed inside your own cloud environment if required.
How long until the assistant is live?
After the free 15-minute discovery call, solution design takes 1 to 2 weeks and build and deploy takes 2 to 6 weeks. Optimize and evolve continues after launch, with workflows monitored against the agreed KPIs.
Can it work with the tools we already use?
Integrations are scoped during solution design, where data flows and integration points are defined before code is written. Connections to systems such as your CRM, helpdesk or calendar are built through APIs and n8n.