Build Conversational Agents Businesses Trust

Most customers go from zero to a testable agent in under 10 minutes. Describe your business process in natural language, and iMorph auto-generates Journeys, Guidelines, Glossary terms, and Tool bindings. You can refine from there — but the cold start is measured in minutes, not weeks.

iMorph supports 7+ languages including English, Chinese, Japanese, Korean, German, Spanish, and Portuguese — with ultra-natural voice synthesis in each. Agents can be deployed to web chat, WhatsApp, phone (voice), API endpoints, and enterprise IM platforms like Feishu, DingTalk, and Slack.

Instead of stuffing everything into one large prompt, iMorph dynamically loads only the rules and knowledge relevant to the current conversation turn. Guidelines are conditionally activated based on context, reducing attention dilution and ensuring strict compliance. Every response is traceable — you can see exactly which rules fired and which knowledge was used.

Yes. iMorph's modeling primitives — Journeys, Guidelines, Glossary, Tools, and Variables — work for any structured conversation. Whether it's outbound qualification, inbound customer service, follow-up orchestration, or appointment scheduling, the same platform adapts to the workflow.

iMorph is designed for high-confidence automation. When the agent lacks sufficient context or confidence, it gracefully escalates — requesting clarification, flagging for human review, or triggering a handoff to a live representative. The system knows when not to answer, which is critical for enterprise trust.

Pricing is based on conversation volume and deployed channels. We offer a free tier for evaluation, a growth plan for scaling teams, and enterprise contracts for organizations needing SSO, audit logs, and dedicated support. Contact our sales team for a custom quote.

iMorph automatically selects the most suitable AI model for each task. The model used depends on factors such as the complexity of the request, whether the interaction is via voice or chat, the language, response speed, reasoning requirements, and any tools that need to be used.

Different stages of the same workflow may use different models to achieve the best balance of quality, speed, and cost. There's no need to choose a single model before building your agent.

Most agent builders help you create a prompt, connect a knowledge base, and publish an AI agent.

iMorph goes much further. It treats every conversation as part of a complete operating system that includes workflows, business rules, approved knowledge, tools, evaluations, conversation traces, and continuous optimisation.

Rather than simply helping you launch an agent, iMorph helps you understand, measure, and improve its performance as your business evolves.

You define the workflows, user personas, expected outcomes, business policies, tool behaviour, and handoff rules you want to test.

iMorph then runs realistic multi-turn conversations across everyday situations, customer objections, and edge cases. It records the results, highlights where things went well or wrong, and provides the evidence needed for review.

Evaluation criteria and scoring should be tailored to each workflow, rather than relying on a single universal quality score.

Once your agent is live, iMorph brings together user feedback, business outcomes, conversation patterns, and detailed request traces to show why the agent behaves the way it does.

This helps your team identify recurring issues, prioritise improvements to prompts, knowledge, tools, or workflows, and validate changes before rolling them out more widely.