Meta Business Agent vs Converiqo AI: Governed Workflows
Meta Business Agent delivers quick conversational AI for consumer businesses inside Meta's messaging apps. Converiqo AI (by Mobiloitte) is an enterprise AI workflow automation platform engineered for regulated industries, cross-channel engagement beyond Meta, and end-to-end back-office execution under your own data sovereignty.
Beyond the Chat Bubble: Why Enterprises Choose Converiqo AI
While consumer messaging agents excel at answering product questions and qualifying retail leads, enterprise organizations require autonomous execution, deterministic policy guardrails, and compliance across complex IT estates.
Regulated Industry Ready
Fully operational for BFSI, healthcare, pharmaceuticals, and public sector—domains explicitly excluded by Meta's enterprise platform terms.
Full-Cycle Operations
Carries conversations directly into ERP procurement, field force dispatch, credit committee approvals, and ticketing with verifiable audit trails.
Zero Data Training
Your enterprise chats are never used to train public models. Features default PII masking, time-limited reveals, and private cloud deployment.
How do Meta Business Agent and Converiqo AI compare at a glance?
| Capability | Meta Business Agent | Converiqo AI (by Mobiloitte) |
|---|---|---|
| Channels | WhatsApp, Messenger, Instagram; agent on website not documented as live | Website, WhatsApp, email, SMS, Instagram, Messenger, Telegram, LinkedIn, and real-time Voice AI |
| Sector eligibility (enterprise tier) | Excludes Finance, Government, Health, Alcohol, Gambling, OTC drugs and matrimony services | Unrestricted enterprise support: purpose-built for BFSI, healthcare, public-sector, and regulated industries |
| Country availability & deployment | "Select markets"; enterprise tier requires an authorized country; no public country list | Global deployment options: Multi-tenant cloud, dedicated private cloud (VPC), or on-premises (India, UAE, EU, US) |
| AI agents per WhatsApp number | One; another active authorized AI agent on the number blocks it | Multi-agent swarm collaboration: multiple specialized agents, routing policies, and numbers managed per workspace |
| Knowledge sources & grounding | Facebook Page, past chats, uploaded documents, catalogues, website; crawled URLs | Authoritative enterprise vector databases, reviewer-approved policies, internal ERP/CRM tables, and live API lookups |
| Knowledge approval and citations | Not publicly documented | Mandatory second-person reviewer sign-off; deterministic dual-pass verification; all answers cite the exact source |
| Testing, staging and releases | Agent Test and Agent Eval; versioning and rollback not publicly documented | Release candidates, pre-deployment scenario suites, immutable release references, and instant one-click rollback |
| Back-office workflow execution | Connectors for commerce, customer systems and scheduling; internal approvals and tasks not publicly documented | Autonomous multi-system execution: approvals, tickets, field force dispatch, procurement POs, and SLA monitoring |
| Model choice & runtime failover | Not publicly documented (proprietary Meta models) | Multi-model orchestration: independently set primary and fallback LLM per stage (OpenAI, Anthropic, Azure, on-prem) |
| Data privacy & training on chats | Meta receives chats to improve AI quality and generate messages; messages kept up to 30 days | Zero AI model training on enterprise chats; default PII masking with reason-logged access; client-controlled retention |
| Security attestations (as worded) | "SOC 2 Type II and ISO 27001 reports" for the WhatsApp Cloud API | Cloud infrastructure SOC 2 Type II & ISO 27001; platform controls aligned; OIDC SSO, MFA, custom least-privilege RBAC |
Choose Converiqo AI if…
Purpose-built for organizations requiring regulatory eligibility, multi-channel reach, and deep operational governance
- Regulated Sector Operations: You operate in financial services, banking, insurance, healthcare, or government—the sectors Meta's enterprise platform terms exclude.
- True Omnichannel Reach: Customers reach you outside Meta's apps: on your corporate website, via email, SMS, Telegram, LinkedIn, or inbound and outbound phone lines.
- End-to-End Enterprise Workflows: The conversation must trigger internal work: multi-level manager approvals, SLA-bound support tickets, field engineer visits, or procurement orders.
- Sovereign Data Controls: Your CISO and DPO require complete control: zero chat training, custom primary and fallback LLMs, masked customer records, and private cloud deployment.
Is your business eligible for Meta's enterprise agent?
The view: a native messaging agent is simple to pilot, but only if your enterprise qualifies under platform policies.
The evidence: Meta's developer documentation explicitly restricts verticals on the enterprise tier: “all verticals are supported except Finance, Government, Health, Alcohol, Gambling, over-the-counter drugs, and matrimony services”. Furthermore, enterprise deployment requires an authorized country profile, which is available only in select markets.
How Converiqo AI solves this: Converiqo AI (by Mobiloitte) is architected specifically for highly scrutinized industries. It powers production agentic workflows for BFSI & Fintech, Healthcare & Life Sciences, and Government & Public Sector organizations. Converiqo AI delivers pre-built compliance playbooks, audited consent registers, and deterministic policy enforcement out of the box.
Whose rules govern the conversation data?
The view: when AI is provided directly by a consumer messaging platform, your customer interactions are subjected to the platform's broader consumer AI terms.
The evidence: WhatsApp's help center informs consumers that “AI from Meta receives chats to improve AI quality and generate messages for this business”. For enterprise buyers, platform-level role-based masking, customer-side audit logs, and granular model choice are not publicly documented.
How Converiqo AI solves this: Converiqo AI operates under strict enterprise data isolation. Your conversation data is never used to train public LLMs. Customer records are masked by default, and unmasking sensitive fields requires an explicit, reason-logged prompt that expires automatically. Administrators select the exact LLM provider for every workflow stage (e.g., Azure OpenAI, Anthropic, or air-gapped on-premises models) with automated fallback routing.
What happens when customers aren't on Meta's apps?
The view: WhatsApp and Instagram are vital channels, but enterprise buyers, patients, and citizens continue to email, call, browse the web, or communicate on professional networks.
The evidence: Meta Business Agent is confined to Meta's consumer apps (WhatsApp, Messenger, Instagram). Native web embed agents, inbound telephony, outbound dialers, email ticketing, and SMS routing are not documented as live capabilities.
How Converiqo AI solves this: Converiqo AI orchestrates a unified agent across nine native channels: Website, WhatsApp, Email, SMS, Instagram, Messenger, Telegram, LinkedIn, and real-time Voice AI. A customer can begin an inquiry on your website, receive a document link over WhatsApp, ask a question via SMS, and speak to an AI voice agent on the phone—all sharing identical context, verified knowledge, and continuous customer state. See the Web AI Agent and Voice AI Agent.
What does the agent do after it qualifies a lead?
The view: qualifying an inquiry in chat is only the first step. Value is realized when the conversation autonomously triggers the back-office processes that fulfill it.
The evidence: Meta's platform provides webhook connectors for commerce and scheduling, but internal approval chains, task assignment, ERP inventory sync, and operational field dispatch are not part of its scope.
How Converiqo AI solves this: Converiqo AI bridges front-office conversations directly to enterprise backends. When a customer confirms an order or service request, Converiqo AI generates ERP purchase orders, dispatches field service technicians with route check-ins and photo proof, opens SLA-tracked support tickets, or routes high-value credit approvals to branch managers. See lead generation automation and procurement automation.
How does a loan enquiry run when Meta's enterprise agent isn't an option?
| Step | Converiqo AI Execution | Why It Matters to a Regulated Lender |
|---|---|---|
| 1. Eligibility question | Answered from the approved product policy, with the source cited | Customers see only what compliance approved; zero hallucinated interest rates or criteria |
| 2. Lead qualification | Scored against the lender's rules and routed to the branch officer for his area, within working hours | No after-hours lead is lost, stalled, or misrouted; automatic advisory scoring |
| 3. Document checklist | An approved template lists the KYC documents; submitted records stay masked by default | Staff see sensitive customer PII only when required and explicitly reason-logged |
| 4. Branch appointment | A visit is booked on the officer's synced calendar, with a WhatsApp confirmation and reminder | Fewer no-shows, zero double-booking, and elimination of manual phone tag |
| 5. Policy exception | A case outside standard credit policy goes to a credit manager as an approval with audit evidence | Every exception and override has a verified approver and timestamp on record |
| 6. Follow-up nurture | A nurture journey respects quiet hours and stops immediately when he books or opts out | Strict contact compliance prevents regulatory harassment penalties |
| 7. Grievance handling | A customer complaint automatically opens a priority ticket with an owner and SLA countdown | Complete, time-stamped escalation trail inspectable by internal auditors and regulators |
Enterprise Security, Governance & Compliance Architecture
Meta Business Agent Assurances
- • WhatsApp Cloud API holds SOC 2 Type II and ISO 27001 reports
- • Messages retained for up to 30 days to operate service
- • Optional local storage setting for designated country hosting
- • Consumer-facing “AI” message badge and stop commands
- • Enterprise access controls and audit logs not publicly documented
Converiqo AI Enterprise Governance
- • Strict Access: Custom least-privilege roles, OIDC SSO, and MFA
- • Record Masking: Sensitive data masked by default with reason-logged reveal
- • Full Audit Trail: Every configuration change logged by actor and action
- • Consent Controls: Scoped consent per channel with quiet-hour enforcement
- • Sovereign Hosting: Multi-tenant, dedicated VPC, or air-gapped on-premises
Converiqo AI is architected to satisfy compliance requirements under India's Digital Personal Data Protection (DPDP) Act, the European Union GDPR, and the UAE Personal Data Protection Law (PDPL). Learn more about our security and data compliance.
Can both run in the same organization?
Yes, when partitioned across dedicated business numbers. A common architectural pattern is deploying Meta Business Agent on top-of-funnel marketing numbers for quick consumer Q&A, while dedicating primary support, loan underwriting, post-sales service, and internal operations numbers to Converiqo AI.
Converiqo AI Enterprise Deployment Methodology:
- 1Access & Roles: Provision OIDC SSO and least-privilege RBAC.
- 2Business Rules: Configure qualification, routing, and approvals.
- 3Approved Knowledge: Ingest and verify corporate policy documents.
- 4Channel Setup: Verify numbers, webhooks, and email gateways.
- 5Team Queues: Establish escalation targets and triage routing.
- 6Scenario Validation: Execute end-to-end release candidates.
Frequently asked questions
Not sure if Meta's agent is enough? Book a 30-minute AI Workflow Audit
Bring one customer journey. We'll show which parts Meta's agent can handle, where your sector, channels, or controls require more, and what the full journey looks like on Converiqo AI.