T7 builds AI support systems that resolve conversations, not just answer them — grounded in your knowledge base, wired into your CRM, measured on deflection and CSAT.
Support teams are drowning in repetitive tier-1 tickets while enterprise customers wait days for a response on the issues that actually matter.
Off-the-shelf chatbots hallucinate, escalate poorly, and can't act inside your systems — so agents end up doing the work twice.
We ship a RAG-grounded copilot that reads your help center, policies and past tickets — with citations, escalation routing and CRM writeback.
For voice, we deploy sub-800ms latency agents that handle authentication, intent capture and warm-transfer to a human on ambiguous cases.
Every deployment ships with a deflection dashboard, a hallucination-rate SLA and an evaluation suite tied to CSAT.
We index your Zendesk / Freshdesk / Intercom articles, product docs and past resolved tickets into a vector store with permissions preserved.
The copilot classifies intent, retrieves relevant context and either resolves in-channel or opens a pre-filled ticket for a human.
Weekly evals measure resolution rate, escalation quality and hallucination — feeding retraining and prompt updates.
Custom AI chatbots trained on your data — web, WhatsApp, Slack and beyond.
Explore serviceHuman-sounding AI voice agents for inbound and outbound calls at scale.
Explore serviceProduction-grade GPT, Claude, Gemini and open-source LLMs — grounded in your data.
Explore serviceTypical pilot: 4–6 weeks from kickoff to a measured deflection number in production on a scoped channel.
No — we sit on top of Zendesk, Freshdesk, Intercom or Salesforce. Existing agent workflows are preserved and the copilot writes back into your system of record.
Every answer is grounded in retrieved sources with citations, gated by a confidence threshold and a topic-scope guardrail. Out-of-scope questions are escalated, not guessed.
Industries where this workflow ships, the insights behind it, and the tradeoffs to weigh.
From AI prototype to production
AI for developers, brokers and property managers
AI for operators and communication platforms
How to design, build and deploy AI agents that plan, call tools and take real actions inside enterprise workflows — without breaking production.
Model routing, prompt compression, caching, distillation and eval-driven downgrades — the levers we use to bring enterprise LLM bills under control without hurting quality.
Text-based chatbots vs voice AI agents — which channel fits your workflow?
How OpenAI's GPT models compare to Anthropic's Claude for enterprise workloads
Talk to a senior AI consultant from T7 about your industry, workflow, or product idea. Free, no commitment — reply within one business day.