Call recording done right - securing, retrieval and search at scale!

Everyone wants voice AI that sounds human, and nobody wants to talk about what happens to those recordings afterward. The irony is that call recordings are probably the most valuable asset your voice infrastructure produces, and most teams are treating them as the last logs.

Here's the uncomfortable truth: If you can't reliably store, retrieve and search your call recordings, you are sitting on a compliance time bomb while simultaneously throwing away business intelligence for which competitor would kill.

The stream ID is Your North Star

The first thing that changed how we think about call recordings at Sayna is understanding that a single identifier, the stream ID, should be the key to everything: every call has a stream ID; every transcript message references this stream ID; every recording chunk knows which stream it belongs to.

This seems obvious until you realize how many voice platforms scatter this context across multiple systems. You end up with audio files which don't know which transcript they belong to, transcripts that can't find their recordings and metadata floating in some third database hoping someone will reunite it with its family.

Your stream ID should be the primary key for your entire voice data lifecycle. Audio. Transcripts. Metadata. Analytics. One ID to rule them all

When you receive a transcript message from your STT provider, that message carries the stream ID. When you save the recording, index it by stream ID. When you need to pull a call for compliance review six months from now, query by stream ID. This is how you avoid the panic of "Where is this recording" that strikes every voice team at 2 AM during an audit.

Storage Architecture That Doesn't Make You Cry

Let me save you from repeating our mistakes. The naive approach is to dump everything in a single S3 bucket organized by date. Seems logical. Works fine until you have a million recordings and someone asks "find me all calls from customer X in Q3 where they mentioned our competitor."

The architecture that actually scales looks more like this:

Hot storage for recent recordings, typically the last 30 days, are the ones that people actually need to access: low latency, higher cost but indexed for fast retrieval.

Warm storage for the 30-day to 6-month window - still accessible within seconds - but optimizing costs over speed - most compliance requests fall in this range.

Cold storage for anything older than 6 months, archive pricing, retrieval measured in hours, not seconds. But here's the thing: you still need to be able to find what you're looking for. Metadata indexing is non-negotiable even for cold storage.

The common failure mode? Teams archive recordings without preserving searchable metadata, then they get a legal hold request and suddenly they defrost terabytes of recordings just to grep through them... Don't be that team

Transcripts Are More Important Than Audio

I know this sounds backwards, the recording is the source of truth, right? Legally yes, operationally, no.

Your transcripts are what makes recording useful - they're what you search, they're what you analyze - they're what you feed into your analytics pipeline - the audio is there for verification and compliance but the transcript is what you actually work with each day.

This changes how you should think about storage priorities: your transcript storage needs to be fast, searchable and always available: and your audio storage can be tied but never let transcripts be disconnected from their recordings: that stream ID link is sacred.

When Sayna delivers transcript messages through the WebSocket, each message is tagged with its stream context. You're not only receiving text, but text that knows where it came from and can be reunited with its audio at any moment - this is by design and not by accident.

PII Redaction Is Not Optional

A quick reminder about this: If you are recording calls and storing transcripts without a PII redaction strategy, you are building a compliance compliance factory.

The regulations are not messes, for example, HIPAA violations can hit $1.5 million for each violation and GDPR fines can reach €20 million or 4% of global annual revenues. Non-compliance with PCI-DSS puts your entire payment processing at risk.

But here's what most teams get wrong: they think about PII redaction as a postprocessing step: record everything, store everything, then later run some redaction work. This approach has two fatal flaws.

First, you have already stored the unredacted data, even if you redact it later, the original exists in backups, logs and probably some engineer's local test environment. Second, your redaction job is always catching up: there is a window where raw PII is locked in your system unprotected.

The better approach is to redact in flight: sensitive information should be identified and handled before the transcript arrives in storage before the audio is archived. This is especially important for the dual-channel problem: you might redact the customer saying their SSN on his audio track but if the agent re-repeates it on his channel, you have unredacted PII in your final recording.

The rule is simple: when PII touches storage it should already be redacted, no exceptions, no "we'll fix it in post"

What needs to be erased? More than you think. Names, addresses, phone numbers, email addresses, Social Security numbers, credit card numbers, medical record numbers, account numbers, birthdates. Basically anything that could identify a person or compromise their financial or medical security.

Search That Actually Works

It is useless to have recordings if you can't find them, and that is where most voices fall completely apart.

The baseline requirement is being able to search by metadata: date range, Stream ID, Caller Number, Agent ID, Call Duration, but that is just table stakes - real search capability means you can query the content of conversations.

Find all calls where customers mentioned switching to a competitor."

"Show me calls when the agent offered a discount, but the customer still cancelled."

"Pull every call from the Healthcare vertical that mentioned appointment scheduling."

This requires that your transcripts be indexed in a way that supports full-text search at least and ideally semantic search for more nuanced queries, like Elasticsearch, OpenSearch or a vector database if you go the embedding route.

The architecture decision here is about latency versus cost. Real-time indexing means instant searchability but higher compute costs. Batch indexing is cheaper but introduces delay. For most production voice systems, near real-time indexing with a 1-5 minute delay hits the sweet spot.

The Compliance Timeline You Need to Know

Different industries have different retention requirements, and violating them goes both ways: Store too little, you are non-compliant; Store too long, you are also non-compliant (hello GDPR right to be forgotten).

Financial services: typically 5-7 years depending on the specific regulation. SEC Rule 17a-4, MiFID II, and Dodd-Frank all have opinions about how long you need to keep these recordings.

Healthcare: HIPAA does not define exact retention periods, but states often do, and they vary wildly: some states require 7 years from the date of service, others 10 years after last treatment of the patient.

General consumer: GDPR requires that you don't keep data longer than necessary for its purpose, which is beautifully vague and absolutely requires legal interpretation for your specific use case.

Practical implementation is building retention policies that are configurable per tenant, per call type, per geographic location. One-size-fits-all retention will either leave you non-compliant somewhere or storing way more data than you need.

Making Recordings Actually Useful

Beyond compliance, there's an entire world of value locked in your call recording that most teams never access.

Train agents. Pull examples of excellent calls for onboarding new hires. Identify common patterns in calls that go poorly. Build coaching materials from real conversations instead of hypothetical scenarios.

Product intelligence – What features are customers demanding that don't exist? What competitor names are most frequently mentioned? What objections do your sales team repeatedly encounter?

Quality assurance. Automated scoring of agent performance. Detection of script compliance. Measurement of resolution rates correlated with conversation patterns.

And here's the thing: none of this is possible if your recordings are scattered across systems, unsearchable and disconnected from their transcripts. The technical foundation has to be solid before you can build the intelligence layer on top.

The Sayna Approach

What we have built at Sayna treat the stream ID as the fundamental unit of organization: every transcript message, every audio chunk, every piece of metadata is linked to this identifier. When you need to reconstruct a call everything is findable

The WebSocket API delivers transcript events in real-time, tagged with their stream context, so your application can process these immediately, store them with proper indexing, apply PII redaction and maintain the chain of custody that compliance requires.

We're not storing your recordings for you, that's intentional: Your recordings should reside under your control, with your retention policies in your infrastructure, what we provide is the infrastructure to make capturing, processing and organizing that data straightforward.

The complexity of voice data management shouldn't require a dedicated team and six months of development, it should be a solved problem you configure once and trust it to work: that's the goal.

Stop Treating Recordings as an afterthought

If you are building voice AI, call recording architecture deserves the same attention that you give latency optimization or model selection. It's not glamorous work and won't demo well, but it's the difference between a production-ready voice system and one that is waiting for its first compliance incident.

Fundamentals are straightforward: unified stream IDs, tiered storage, in-flight PII redaction, searchable transcripts, configurable retention. Get these right and you have built a foundation that scales.

Get them wrong and you've built a liability factory that happens to make phone calls.

Your choice.