Haptik vs Converiqo AI: Who Controls Knowledge & Data?

The view: in many deployments, the vendor's team configures the knowledge and the client asks for changes. That slows fixes and blurs accountability.

The evidence: Haptik's agents learn from PDFs, CSVs, blogs and knowledge bases, with integrations to Zendesk Guide, Freshdesk, Salesforce Knowledge and USU. Its documentation describes a Knowledge Connector, marked BETA and WhatsApp-only, that answers from up to 15 PDFs and highlights the relevant passage, enabled through Haptik's point of contact. A knowledge-approval workflow is not publicly documented. Converiqo AI (by Mobiloitte) has a Knowledge Editor role. Editors submit content, a different authorised reviewer approves it, and answers cite the approved source. Editors work the approval queue daily, with specific rejection notes.

The view: Haptik has solid release basics, and deserves credit for them.

The evidence: Haptik documents staging and production environments, named versions, “Restore on Staging” to roll back, and a separate Bot Builder Publish role. A self-serve test or regression suite, and a publish-approval workflow, are not publicly documented. Converiqo AI builds each change as a release candidate, checks dependencies and knowledge, runs scenario tests for lead capture, booking and handoff, and records a release reference. For voice, a test console runs interruption, silence, handoff and action-confirmation scenarios before launch-readiness checks.

The view: model flexibility protects both quality and continuity.

The evidence: Haptik lets enterprises choose between models such as GPT, Llama and Claude. Per-stage model routing and bring-your-own model keys are not publicly documented. In Converiqo AI, administrators select a primary and a fallback model for each runtime stage. They test multi-turn scenarios in a RAG lab, and record QA verdicts on answers that need review. Insights track grounding, latency and unanswered questions.

The view: in B2C businesses, many people touch customer conversations every day.

The evidence: Haptik documents predefined roles by tool, a downloadable audit dashboard, IP whitelisting, and hidden fields that mask chosen data from agents, though “Name and Platform fields can't be masked”. Custom roles, MFA and configurable retention are not publicly documented. Converiqo AI (by Mobiloitte) lets the client admin define custom roles that grant only the actions and records a job needs, and enforce MFA. Records are masked by default, and a protected record opens only through a time-limited reveal with a written reason, shown in the client's operator-access log.

The view: the same governed AI layer can run internal work.

The evidence: Haptik publishes an IT service desk use case for L1 queries, access management and incidents. HR, procurement, field-service and vendor workflows are not publicly documented. Converiqo AI covers employee self-service, procurement from request to purchase order, field-force dispatch with proof of service, and vendor support. See employee self-service automation and procurement automation.