Tool & function calling
We connect the agent to real systems: order lookup, stock checks, record creation, sending email. Every tool gets input validation and permission checks.
AI & LLM
Unlike a chatbot, an agent gets work done: it searches your knowledge base, creates records in your CRM, books appointments, checks orders and hands over to a human when it should — in 50+ languages, around the clock.
We connect the agent to real systems: order lookup, stock checks, record creation, sending email. Every tool gets input validation and permission checks.
The agent draws on your product documentation, policy texts and past support tickets, and answers with the source attached.
Website widget, WhatsApp, Instagram, email, Slack, Teams, or inside your own application — one agent, one knowledge base, consistent behaviour.
The agent knows its limits. On uncertainty, signs of frustration or an off-policy request it summarises the conversation and hands it to a live agent — the customer never has to start over.
Behaviours like committing to a price, disclosing personal data or promising a refund are blocked at the guardrail layer. Every conversation and action taken is logged.
Unanswered questions, conversations flagged as unsatisfying and handoff rates are reported; the knowledge base and instructions are updated accordingly.
01
We define in writing what the agent will resolve, where it stops and what it must never do.
02
Knowledge sources and business systems are connected, with test scenarios written for each tool.
03
We run it against your real question archive, correct wrong answers and probe the guardrails.
04
We ramp traffic gradually and watch resolution and handoff rates on the dashboards.
We reduce that risk in three layers: answers are generated only from approved sources, on critical topics the agent hands over rather than committing, and everything is logged. Before launch you also get a measured accuracy report against your own question archive.
We can connect to almost any system with an API or database access. Common platforms have ready integrations; for bespoke systems we write an adapter layer.
Fine-tuning, LoRA/QLoRA, instruction tuning, DPO and evaluation
Models that run on your own servers and keep data in-house
Answers grounded in your own documents, with citations
In a short call we listen, then tell you plainly which approaches fit your situation and which do not. We reply within 24 hours.