AI Agents For Business Operations Resources

Transcription is an area that does come up in our reviews. We treat it as core product work, not a support queue ticket. We continuously retrain and tune the models behind Sidd’s transcription, with a particular focus on accents, dialects, and edge cases like alphanumeric identifiers, the most common gaps flagged by users. Sidd is also built with a human-in-the-loop model, so agents stay able to review and adjust what’s captured rather than depending on the transcript alone. If a specific accent, language, or use case is causing repeated issues for your team, your Laivly account team can prioritize it. That’s the kind of input that has shaped past accuracy updates.

Genesys Cloud CX, Talkdesk, and NICE CXone are platforms many contact centers already run their interactions on: routing, telephony, ticketing. Laivly isn’t a replacement for that. It’s the AI infrastructure that runs on top of it, and the AI doing the work at the same time. Sidd functions as a robust agent assist, as well as an autonomous AI agent for end-to-end resolution. But it also acts as the orchestrator that bridges what you’re running now with whatever comes next, so as the technology changes or your priorities shift, those capabilities move, adjust, or expand instead of forcing a new deployment from scratch. Most AI tools solve one problem and stall when that’s no longer enough. Sidd is built to keep doing the work and keep evolving at the same time. Because it operates at the interface level instead of through APIs, all of this extends to systems your CCaaS platform doesn’t natively reach—including legacy or homegrown tools—without ripping out what’s already running your operation.

Has anyone used AI agents to build an MVP from internal documentation? I'm interested in best practices for protecting sensitive information while still getting useful results. How do you balance productivity with privacy?