Assistants that actually help — grounded in your knowledge and systems, honest about what they don’t know, and safe to put in front of customers and staff.
Bolting a raw LLM onto an FAQ produces a confident liar. Enterprise conversational AI has to be grounded in real knowledge, integrated with real systems, and disciplined about escalation — or it damages the brand it was meant to help.
Answers come from your content and data via retrieval, not the model’s imagination.
Real value is checking an order, booking a slot, opening a ticket — connected to your systems.
A good assistant escalates gracefully instead of guessing on high-stakes questions.
We build conversational AI on a retrieval foundation so answers are grounded in your actual knowledge base, connected to your systems via tools so the assistant can do things, and designed to hand off to a human the moment it should. Deployed across chat and voice, with the guardrails to run in production.
Answers sourced from your content and data, with the discipline not to invent.
The assistant can look things up and take actions in your systems, not just talk.
One assistant across web, messaging, and voice channels.
Clean handoff to a human with full context when it matters.
Scope, tone, and safety controls tuned to your brand and risk appetite.
See what people ask, where the assistant helps, and where it should improve.
Deflection that doesn’t backfire
Handle routine volume without frustrating customers.
Always available
Consistent help across time zones and after hours.
Grounded answers
Responses tied to your real knowledge, not model guesswork.
Actions, not just answers
The assistant resolves, not just responds.
Brand-safe
On-tone, in-scope, and honest about its limits.
Continuously improving
Real conversation data drives ongoing refinement.
Real, in-production work. Clients are described by sector and scale, per NDA — we don't publish numbers we can't stand behind.
The chat assistant on cone.red is one of ours — retrieval-grounded, tool-calling, and gated to a verified knowledge base so it won’t fabricate figures. Try it.
The same retrieval and evaluation discipline that powers our document and GEO work underpins every assistant we ship.
Feasibility in weeks, production in a quarter — not a nine-month science project.
Define the use cases, the knowledge sources, and the escalation rules.
Ground the assistant, connect the tools, and test answer quality against real questions.
Launch across your channels with guardrails and human handoff live.
Mine real conversations to close gaps and expand what the assistant can do.
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Sheridan, WY, USA • Barcelona, Spain • Lisbon, Portugal
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