An AI agent that handles the full conversation
Qualify leads, answer questions, and book meetings — in a single chat thread, without handing off to a form.
demo ai agent
What it can do
Multi-turn memory
Holds the full conversation history across every message. Ask a follow-up five turns later — it still knows what you meant at the start.
Streaming responses
Replies appear word-by-word as the agent reasons, so the interaction feels immediate rather than transactional.
Tool visibility
Every tool the agent calls is shown in the UI — what fired, what parameters went in, and what came back. No black box.
Saved conversations
Conversations are stored and reloadable across sessions. Come back days later and pick up exactly where you left off.
Tools it calls
Every action the agent takes is backed by a named tool with a defined contract. You can watch them fire in real time by clicking a tool badge in the chat above.
get_user_infoRetrieves the signed-in user's email address and local timezone. Called before any booking or contact action so the agent never has to ask for details the system already knows.
get_available_slotsQueries the Cal.com API for open time slots on a date the user mentions. Returns the list as a formatted table so the user can pick without leaving the chat.
create_bookingConfirms and creates the meeting in Cal.com using the slot the user selected — no form, no redirect, no context switch.
submit_contactSends a structured written inquiry to the team's inbox when the user isn't ready to book. Their email is used automatically; they only have to describe their problem.
What we build for you
Your product becomes an agent
Every SaaS dashboard, internal tool, or web app can have a conversational layer added to it. Users describe what they want — the agent queries your APIs, reads your data, and takes action. Less navigation, less training, less friction. The same product, with an interface that finally gets out of the way.
Customer support that resolves, not just responds
The agent handles tier-1 support end-to-end: looks up the account, checks order status, processes the refund, updates the setting — whatever the action is, it happens in the chat. Only genuinely complex cases reach a human. Your support volume drops; your team works on things that actually need them.
Onboarding that adapts to each user
New users describe their goal and the agent configures their setup, surfaces the right features, and answers questions as they come up — instead of making everyone follow the same static walkthrough. Completion rates go up. First-week drop-off goes down. Support tickets about 'how do I do X' mostly stop.
Ready to see this in your product?
What you just tried is production-quality — the same stack, the same standards, and the same attention to detail we bring to every client build. The service page covers how we approach text agents: the full process, what's included, and how we price our work.