I have been spending a significant amount of time integrating Retell AI into backend database applicationf for both read and write and looking to have someone help wme with some of the more complex design issues related to AI voice and the handling of outlier scenarios where callers might deviate from standard expectations . Let me know if you are intereted. Looking for 1-3 hours to start and then ongoing as needed.
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Hi Mgilbert, we love to discuss your needs. Can we have your email so we can contact you directly?
how much would your service be?
I can help you with it. If you can tell provide me more detail so I can guide you to the right direction.
Hi @mgilbert, are you still looking for help with this? As a Diamond Retell Partner, we’d be happy to give you a free Zoom consultation.
@mgilbert — your backend read/write setup and the outlier scenarios you mentioned are exactly where independent QA can be useful.
MARUPA focuses on testing the live Voice AI workflow from the outside and verifying whether the intended business outcome actually happened correctly — especially when callers deviate from the happy path.
That can include whether data was written correctly, whether state was preserved, whether fallback behavior worked, and whether the agent created unintended side effects.
I can start with a small 5-test QA Snapshot on the existing agent so you can evaluate the findings before deciding whether broader QA support would be useful.
Alberto
MARUPA — Independent Voice AI QA
@mgilbert Your read and write concern is exactly where I would start. I design writes to fail closed, so the agent does not confirm a booking or update unless the system verifies it.
I would review the current tool schema, the database result returned to the agent, fallback and human handoff, then convert the known outliers into repeatable eval cases.
Relevant proof: my production voice path reaches about 1.5 seconds warm time to first audio. The platform behind it has 76 edge functions and about 140 Postgres tables. Its release gates currently pass 4 of 4 unqualified lead cases, 3 of 3 abuse stops and 12 of 12 AI CRO eval suite.
I will not claim experience with your exact backend before seeing it, and I will not quote scope until I have read-only access to the current design.
Message me here if the review is still open.
Stone
@mgilbert — Damian Schaeffer, founder of Natyv AI (natyv.ai). US / Eastern Time. I ship production Retell-style voice agents with backend read/write and fail-closed tool calls, so the agent doesn’t confirm a write the system didn’t verify.
Happy to start with a paid 1–3 hour design pass on your outlier paths (tool schema, DB results returned to the agent, fallback/handoff), then ongoing if useful. No rebuild unless the review says you need one.
Email Damian@get-myagent.com or reply here.
Your backend read/write path is the right place to start because the agent must not confirm a booking or update unless the system verifies the write. I propose a fixed $450 diagnostic: five outlier scenarios, verification of database state and fallback/handoff, a reproducible failure ledger, and the three highest-impact fixes within one business day. No production changes in this milestone. Is the 1–3 hour review still open, and can you fund the diagnostic with read-only access? Email kalin.smolichki@gmail.com or DM here.