QMEAI delivers a no‑code platform that lets enterprises fine‑tune large language models on private datasets within an encrypted, isolated environment and deploy domain‑specific chatbots through a visual builder. The solution provides secure data ingestion, role‑based access control, and FastAPI/GraphQL endpoints for seamless integration with CRM, ERP, and help‑desk systems, ensuring compliance while reducing internal search time.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises often struggle to deploy AI chatbots that can answer domain‑specific queries because existing solutions require extensive coding, expose proprietary data to third‑party models, and lack seamless integration with internal tools. This creates bottlenecks in employee productivity and raises compliance concerns.
Solution
QMEAI offers a no‑code platform that lets organizations train large language models on their own private datasets within an isolated, encrypted environment. Users configure data sources, define conversational intents, and launch specialized chatbots through a visual builder, eliminating the need for deep ML expertise. The trained models are hosted on a Kubernetes‑orchestrated cloud stack with FastAPI endpoints, enabling real‑time inference that can be embedded into existing CRMs, intranets, or ticketing systems. Role‑based access control and audit‑ready logging ensure that data governance and regulatory requirements are met while delivering instant, context‑aware answers that reduce employee search time.
Target Audience
The primary customers are mid‑size to large enterprises that need internal knowledge assistants for customer support, IT help desks, and sales enablement, particularly in regulated industries such as finance, healthcare, and manufacturing.
Features
- Secure data enclave that ingests on‑premise or cloud‑based documents, tables, and knowledge bases without exporting raw data
- Automated fine‑tuning pipeline that leverages the latest transformer architectures to produce domain‑specific LLMs
- Drag‑and‑drop chatbot designer with intent mapping, fallback handling, and multi‑language support
- RESTful and GraphQL APIs powered by FastAPI for easy embedding into ERP, CRM, and help‑desk platforms
- Role‑based access control, end‑to‑end encryption, and GDPR‑compatible audit logs for full compliance
- Scalable deployment on Kubernetes with auto‑scaling, load balancing, and PostgreSQL‑backed session storage
- Monitoring dashboard showing query latency, usage metrics, and model performance drift alerts