Anyone using tl;dv in production for a Fortune 500 client onboarding?

Hello everyone! 👋

I've been deep in the weeds of a multi-year project automating and securing the client onboarding pipeline for a major financial services firm (definitely Fortune 500 territory). We handle incredibly sensitive data, and the compliance requirements are, as you can imagine, extensive and non-negotiable.

A persistent pain point has been the knowledge transfer and process documentation phase. Engineers and architects record countless hours of Zoom and Teams calls walking through environment diagrams, security protocols, and integration specs. Manually reviewing these to create runbooks and handoff documents is a massive time sink and introduces human error.

I've been evaluating **tl;dv** as a potential solution to clip, transcribe, and organize key moments from these calls automatically. The promise is huge: tag a "database credential rotation" segment from a 90-minute call and have it instantly available with a searchable transcript for the ops team.

Before I commit to proposing this tool for a production workflow, I'm keen to hear from anyone who has actually implemented it in a similarly high-stakes, regulated environment.

My specific questions are:

* **Security & Compliance:** How does the handling of audio/video data align with strict data residency and privacy policies (think GDPR, CCPA, internal infosec rules)? Is the data processed in a compliant cloud, or can it be kept on-premises/within our VPC?
* **Integration Workflow:** Have you successfully wired the clips and transcripts into other systems? I'm picturing a pipeline where a tl;dv clip triggers an automation. For example:
* A clipped "go/no-go approval" generates a ticket in Jira.
* A transcribed "firewall rule change" instruction is parsed by a script and fed into our Terraform/Tower pipeline.
* Clips are automatically categorized and stored in a specific Confluence space.
* **Reliability & Scale:** Does the tool hold up when processing hundreds of hours of recordings per week? Any issues with accuracy of speaker detection or transcription for technical jargon?
* **Pitfalls & Gotchas:** What weren't you expecting? Permission nightmares? Metadata limitations? Cost scaling that surprised you?

If you've built any glue code (Ansible playbooks, Terraform modules for provisioning, simple Python scripts) to make tl;dv work within a larger IaC/automation framework, I would *especially* love to see snippets. For instance, an example of how you might fetch a new clip via webhook to trigger a downstream action:

```python
# Example: Flask endpoint to receive tl;dv webhook
@app.route('/webhook/tldv', methods=['POST'])
def handle_tldv_clip():
data = request.json
clip_id = data.get('clipId')
transcript = data.get('transcriptText')
tag = data.get('userTag') # e.g., "CREDENTIAL_ROTATION"

# Logic to route based on tag
if tag == "CREDENTIAL_ROTATION":
# Parse transcript for hostnames, users
# Create a ticket or pre-populate a Vault SSH role command
ansible_playbook_path = f"/opt/automation/trigger-rotation.yml --extra-vars 'clip_id={clip_id}'"
# ... execute playbook or add to queue
return jsonify({'status': 'received'}), 200
```

Any insights, war stories, or configuration notes would be immensely valuable. The last thing I want is to introduce a cool new tool that becomes a compliance finding or a siloed island of information.

Thanks in advance for sharing your experiences