Yellow.ai vs Converiqo AI: Operations Beyond Service
Yellow.ai is an enterprise-grade agentic AI platform for customer and employee service, with mature release controls, 25+ channels and six hosting regions. Converiqo AI (by Mobiloitte) is an enterprise AI workflow automation platform that extends past service into procurement, field operations and vendor support. It adds reviewer-approved knowledge and reason-logged access to customer data.
How do Yellow.ai and Converiqo AI compare at a glance?
| Capability | Yellow.ai | Converiqo AI (by Mobiloitte) |
|---|---|---|
| How it describes itself | "Enterprise-Grade Agentic AI Platform"; "AI Agents for CX and EX Automation" | Enterprise AI workflow automation platform |
| Customer service | Supported | Supported |
| Employee service (HR, IT) | Conversational EX Cloud | Supported (employee self-service with verified requester groups) |
| Procurement, field force, vendor support | Not publicly documented | Packaged procurement, field force dispatch, and vendor self-service modules |
| Channels | 25+, including Teams, Slack, LINE, Viber and APAC marketplaces; WhatsApp calling and RCS | Website, WhatsApp, email, SMS, Instagram, Messenger, Telegram, LinkedIn, voice |
| Knowledge approval and citations | Not publicly documented | Second-person reviewer approval; answers cite the approved source |
| Release control | Sandbox, staging and live, approver sign-off and revert | Release candidates, dependency validation, scenario tests, release reference |
| Model choice | Bring your own OpenAI, Azure OpenAI, Bedrock or Anthropic account, per environment | Primary and fallback model per runtime stage with automated failover |
| Roles and sign-in | Predefined roles; Google, Microsoft, ADFS and Azure AD SSO; custom roles and MFA not publicly documented | Custom least-privilege roles, OIDC SSO, MFA |
| Access to customer data | PII masking on the data layer; randomised names in chat logs | Masked by default; time-limited reveal with a recorded reason; client-visible access log |
| Conversation retention | Six months, then archived; configurability not publicly documented | Configurable retention; scoped erasure with typed confirmation |
| Deployment | SaaS hosted in the US, EU, Singapore, India, Indonesia and UAE; private cloud or on-premises not publicly documented | Cloud, private cloud or on-premises |
| Certifications (as worded) | SOC 2 Type II, ISO/IEC 27001:2022, ISO/IEC 27701:2019, PCI-DSS 4.0.1, HIPAA | Cloud infrastructure SOC 2 Type II & ISO 27001; platform controls aligned |
Choose Converiqo AI if…
- Operations Beyond CX & EX: AI has to run operational workflows, such as purchase requests, field force dispatch, route tracking, and vendor queries, not only service conversations.
- Auditable Knowledge Approval: Every answer must trace back to approved content that a second authorized reviewer signed off, complete with transparent source citations.
- Reason-Logged PII Access: Your privacy team wants each look at a customer record justified, logged with an explicit business reason, and visible to the client in an access log.
- Private Cloud & Gulf Operations: You require private cloud or on-premises air-gapped deployment, or native Arabic and English conversations with right-to-left rendering for Middle East operations.
What happens beyond customer and employee service?
The view: most enterprise AI platforms stop at the service desk. The next efficiency gains sit in operations: buying, dispatching and supplier support.
The evidence: Yellow.ai has a dedicated employee-experience product for IT support, password resets, hardware requests, HR policy, leave and payslips. We found no public documentation of procurement, field-service or vendor workflows. Converiqo AI (by Mobiloitte) runs procurement from purchase request through approval, RFQ, quote comparison and purchase order. Its dispatch board assigns field jobs with routes, check-in, check-out and proof of service, and vendor enquiries are handled as tracked support. See procurement automation, field force automation and vendor self-service automation.
How is AI knowledge approved before customers see it?
The view: syncing a knowledge base is easy; deciding what is allowed to go live is the governance problem.
The evidence: Yellow.ai's knowledge base, Atlas, ingests files, URLs, sitemaps and third-party sources such as ServiceNow, with metadata tagging and scheduled syncs. A step that approves knowledge before it goes live, and citations shown to end users, are not publicly documented. In Converiqo AI, content sits in an approval queue until a second authorised reviewer approves it. Answers cite the approved source, and questions the assistant could not answer become draft FAQs that go through the same approval.
Do both platforms control releases properly?
The view: here, both are strong.
The evidence: Yellow.ai documents Sandbox, Staging and Live environments, publish requests that approvers accept or decline, selective publishing and revert. Its AI Trust Centre adds evaluators, traces, AI-generated test cases and mock APIs. Converiqo AI packages each change as a release candidate with its flow and dependencies. It validates the candidate against knowledge and business data, runs scenario tests and records a release reference. It applies the same approval discipline elsewhere: nurture journeys are simulated and approved, campaign authors and approvers can be different people, and surveys are published as versioned instruments.
How is day-to-day access to customer data controlled?
The view: privacy incidents often start with legitimate staff looking at more than they need.
The evidence: Yellow.ai documents PII masking on the data layer, randomised names in conversation logs, predefined roles and enterprise SSO. Chats are retained for six months and then archived. Custom roles, MFA and configurable retention are not publicly documented. In Converiqo AI, records are masked by default. An operator who needs a protected record enters a reason, opens a time-limited window and closes it. The client reviews that access in an operator-access log. Retention is configurable, and erasure previews its exact scope and requires a typed confirmation.
Where can each platform be deployed?
The view: for banks, government bodies and Gulf enterprises, where the platform runs can matter as much as what it does.
The evidence: Yellow.ai hosts its services and data in the US, EU, Singapore, India, Indonesia and UAE. We found no public documentation of private-cloud or on-premises deployment. Converiqo AI (by Mobiloitte) can be deployed in the cloud, in a private cloud or on-premises, and supports Arabic and English conversations.
How would a Dubai logistics company run on each platform?
| Moment | Yellow.ai (as documented) | Converiqo AI (by Mobiloitte) |
|---|---|---|
| A shipper, Khalid Al Mansoori, asks in Arabic where his consignment is | Customer service agent, with ticket creation | Answer from tracking data through the API, in Arabic, citing the approved delivery policy |
| The delivery fails and needs a new slot | Actions through prebuilt integrations and APIs | A new slot is booked and a field job goes to a driver, with route, check-in and proof of delivery |
| A driver asks about leave and a payslip | EX Cloud | Employee self-service with verified requesters |
| A subcontracted carrier queries an unpaid job | Not publicly documented | A vendor support ticket with an owner and a resolution target |
| The depot runs low on packaging | Not publicly documented | A purchase request goes through approval, RFQ and quote comparison to a purchase order |
How does each handle security and compliance?
Yellow.ai publishes a broad certificate set, a DPA covering GDPR and UK GDPR, TLS in transit, keys in vaults, WAF and DDoS protection, and annual third-party penetration tests.
Converiqo AI (by Mobiloitte) operates on SOC 2 Type II and ISO 27001 certified cloud infrastructure, with application controls aligned to enterprise standards. It provides OIDC single sign-on, MFA, custom least-privilege roles, an audit log by actor and action, masked records with reason-logged access, consent records by channel and purpose, and scoped erasure. It is designed to support obligations under India's DPDP Act, the EU GDPR and the UAE PDPL. See security and data compliance.
How does Converiqo AI run once live?
Administrators get a health dashboard with integration readiness and support risk, plus provider health and delivery events for every channel. Failed operations are checked before retrying. Structural changes, such as switching vertical packs, show an impact preview, take a snapshot and keep a rollback path. A role-scoped Copilot answers operational questions and links to the records behind each answer.
Can Converiqo AI run alongside Yellow.ai?
Yes. Some enterprises keep Yellow.ai for high-volume customer service and add Converiqo AI for procurement, field and vendor workflows. The two connect through scoped API keys and verified webhooks. Teams that consolidate usually move one journey at a time: access and roles, business data, approved knowledge, channels, team queues, then tested end-to-end journeys before live traffic moves.
Frequently asked questions
Bring one service-plus-operations journey to a 30-minute AI Workflow Audit
We'll map a journey that starts with a customer message and ends in operational work, such as a redelivery, a vendor query or a purchase order. You'll see where Converiqo AI takes it further than a service-only platform.