Implementation Status Categories
Every aspect of AgentFlow falls into one of four categories. Use these definitions to interpret any claim made in public documentation or a private walkthrough.| Category | Meaning |
|---|---|
| Implemented | Built and represented in the private product foundation. Suitable for private evidence review under appropriate confidentiality terms. |
| Verification needed | Requires live provider evidence, end-to-end testing, or buyer-side confirmation before any commercial claim can be made. |
| Planned | Represents the product direction and a reasonable next step in development. Not complete unless separately verified during a private review. |
| Not claimed | An area where this public documentation makes no certification, customer, revenue, or audit claim whatsoever. |
When in doubt, treat a capability as verification needed until you have seen live evidence. This protects you and creates a productive basis for the private review conversation.
What to Verify in a Technical Review
Work through each area below during your evaluation. These are the signals that separate a production-conscious SaaS foundation from an unfinished build.Product Workflow Completeness
Verify that the full path from lead intake through AI qualification, operator review, billing readiness, and CRM or workflow handoff is represented in the product — not just described in documentation.
Authentication and Dashboard Behavior
Confirm that protected operator-facing areas require authentication, that unauthenticated access is blocked, and that the dashboard experience is consistent with the product claims made publicly.
Tenant-Aware Assumptions
Identify whether the architecture supports multi-tenant access boundaries, and understand what isolation model exists — or what a buyer would need to implement — before multi-client deployment.
Payment and Checkout Readiness
Verify the payment integration against a live provider account. Checkout readiness in documentation should be backed by test-mode evidence showing payment flows actually process correctly.
Webhook Safety Behavior
Confirm that webhook handling enforces signature verification, processes events server-side, and treats incoming provider events as a trust boundary. Do not accept public documentation as sufficient evidence here.
AI Qualification Behavior
Review how the AI qualification step behaves with realistic lead inputs — including edge cases. Understand the cost profile per qualification call, the data handling approach, and what prompt governance controls are in place.
Deployment Posture and Rollback
Understand the deployment environment, hosting configuration, and what a rollback or recovery looks like if a deployment fails. Verify this against actual deployment evidence, not just described posture.
Logging, Monitoring, and Alerting
Check whether operational logging is in place, whether there is a monitoring layer that would surface errors in production, and whether alerting is configured for critical failure paths.
Test Coverage and Known Gaps
Request the test coverage picture — what is tested, what is not, and what known gaps exist. Every production-conscious codebase has known gaps; the question is whether they are documented honestly.
Error Handling and Support Model
Understand how the product handles errors in the workflow — failed AI calls, payment failures, webhook delivery failures — and what the operational support model looks like for a deployed client or customer.
Evidence to Request During Private Diligence
Once you move into a private review, make these requests explicitly. A well-prepared seller should be able to respond to each one.Product walkthrough with realistic lead scenarios
Ask to see the product run through actual lead scenarios — not a curated demo path. Include edge cases: incomplete lead data, disqualified requests, and operator review decisions.
Source review under NDA
Request a structured code review session once a confidentiality agreement is in place. Focus on the areas with the highest operational risk: authentication logic, webhook handling, AI integration, and payment flows.
Payment provider test evidence
Ask for test-mode evidence from the payment provider — screenshots, logs, or a live walkthrough — showing that checkout flows process correctly end to end.
Webhook validation evidence
Request evidence that provider webhooks are validated at the server boundary, not just received. Signature verification is the minimum bar.
AI provider behavior and prompt governance review
Review how AI qualification calls are structured, what data is sent to the provider, and what controls exist around prompt behavior. Understand the latency and cost implications at realistic lead volumes.
Known-risk register
Ask for a documented list of known risks, open issues, and areas that the seller considers incomplete or requiring buyer attention after acquisition or licensing.
Initiating a Private Review
When you are ready to move from public evaluation into a formal technical review, reach out directly:- Email: contact@agentflow-enterprise.com
- Book a call: cal.com/ciprian-stefan-plesca