AI Chatbot Testing Portal

Our Story

We design, build and scale chatbots and conversational platforms for businesses of all sizes. From early prototypes to enterprise-grade deployments, our focus has been on user-centric design, data privacy and measurable business outcomes.

Milestones

  • 2016
    Founded
    ConverseAI Labs started in a small co-working space, founded by AI engineers and UX designers who believed conversational interfaces would change how people interact with software.
  • 2017
    First Enterprise Pilot
    Completed a pilot chatbot for a mid-size bank to automate customer FAQs and balance inquiries — reduced average response time from hours to seconds.
  • 2018
    Multilingual Expansion
    Launched multilingual NLU capabilities covering English, Hindi, Spanish and French to serve global clients.
  • 2019
    Omnichannel Platform
    Released an Omnichannel ChatOps platform integrating web chat, WhatsApp, and voice assistants with analytics.
  • 2021
    Enterprise Partnerships
    Signed 10+ enterprise customers in finance, healthcare and retail. Introduced secure on-prem deployments.
  • 2023
    Human-in-the-loop & Low-Code Studio
    Launched a low-code bot-builder and human-in-the-loop review system for continuous learning and compliance.
  • 2025
    State-of-the-art LLM integrations
    Integrated latest LLMs for contextual reasoning and industry-specific knowledge graphs to deliver better explainable answers.

Why chatbots? (Our philosophy)

  • Make complex services simple: users should get answers in one or two messages.
  • Human-in-the-loop learning ensures continuous improvement.
  • Privacy-by-design — we minimise data collection and enable on-prem deployments.
  • Design first: language is UX — we craft microcopy and flows that reduce frustration.

Technology & Approach

We combine intent & entity models, contextual session state, knowledge graph retrieval, and LLM-based reasoning for complex queries. Our typical stack includes: Docker/Kubernetes, Python (FastAPI), Redis for session store, vector DB for embeddings, and secure OAuth + RBAC for enterprise access.

Notable case studies

Retail Assist — 24/7 Sales Assistant
Deployed a product discovery chatbot that improved click-through to product pages by 36% and increased conversion rate for assisted sessions by 18%.
HealthHelp — Triage & Scheduling
A symptom triage bot that reduced call-center load by 42% and decreased wait-times for appointments.

Awards & Press

  • 2020 — Best Conversational AI Startup - TechAwards
  • 2022 — Innovation in Customer Experience - CX Summit

Values & Ethics

We build conversational systems that are safe, explainable and comply with regulatory requirements. We follow a values-first product process:

  • Transparency: Users should know they are talking to a bot and be able to ask for a human.
  • Fairness: We audit models for bias and maintain human oversight.
  • Data minimization: Collect only what's needed for the task and store it securely.

Looking ahead

Our roadmap includes multimodal assistants (image + text), stronger verification for critical workflows (finance/health), and deeper vertical models for domain-specific conversations.