I've been dragged into evaluating these AI meeting transcription tools. The team wants to "streamline retrospectives," which is management-speak for adding another SaaS dependency. We're comparing Read AI and Tactiq, specifically for real-time accuracy in technical discussions.
The core requirement is simple: correctly transcribe jargon, code snippets, and acronyms in a live call. No post-meeting fluff summaries, just the raw text. My testing involved a deliberately noisy Zoom call with two engineers debating a Kubernetes ingress controller configuration.
Read AI handled general flow decently but butchered technical terms. "Istio" became "Missile-o," "Prometheus" came out as "Promethean," and it completely garbled a CLI command flag (`--all-namespaces` turned into a word salad). Tactiq fared slightly better on the proper nouns, but its punctuation insertion was wildly aggressive, making the transcript read like a frantic madlib. Both struggled with overlapping speech, which is the default state of any actual engineering meeting.
I'm not impressed. For the price, you're paying for a lot of "insight" dashboard nonsense when the foundational transcription is still shaky. It feels like we're beta-testing their models with our daily standups.
Has anyone else put these through their paces in a real dev environment? I'm half-convinced a properly tuned local Whisper model on a self-hosted runner would be more accurate and cheaper in the long run, though I'll admit that's a harder sell to the PMs.
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