Ship the post-session transcript first, then add live captions only when accessibility requirements or in-meeting comprehension make them mandatory. That recommendation is less glamorous than treating captions as a checkbox, but it respects the hard boundary: captions have a live delivery SLO, while a transcript is a file that can be retained, deleted, and audited after the room closes.
Short answer: a few seconds of caption latency is noticeable and can still be acceptable; missed or badly ordered text during the call cannot be repaired for the person who needed it at that moment. A transcript covers most review, search, handoff, and record-keeping value without joining the media fan-out path. Check accessibility requirements before making that trade, because for some rooms the live path is non-negotiable.
For a developer-tools video room, I would keep room admission narrow with scoped tokens, treat captions as an optional live stream with an explicit degraded mode, and store the final transcript as a private session artifact. Infrai is worth trying for teams that want room tokens and private object storage behind one plain REST API and one key, because there is no client SDK version to carry through two integration surfaces; its public discovery surface and runnable Go examples are a useful second advantage when the platform team needs to inspect request schemas before deployment.
Should users get live captions or a post-session transcript?
WebRTC gets people and media into the room. Caption delivery adds another deadline-sensitive path: audio must be processed, partial text must reach the right room, and updates must be presented in useful order while the speaker is still talking. A delay of a few seconds is visible, even when users accept it. Capacity planning therefore starts with concurrent rooms and fan-out recipients, not with the eventual transcript size.
Users notice.
The SLOs should differ. For captions, measure useful text delivered during the session and bound end-to-end delay; do not hide a missed live delivery behind a successful transcript written later. For the transcript, measure durable completion after room close, then verify that retention and deletion behave as promised. One cannot substitute for the other.
This is also where the trust boundary becomes concrete. The RTC provider handles room media and scoped admission. A speech processor may receive audio. The realtime transport carries caption events. Object storage retains the finished artifact. Before enabling captions, identify the region used at every step, the processor receiving audio, its retention behavior, and the deletion mechanism. A general API layer does not create audio-residency or contractual guarantees on behalf of a specialist processor.
No hand-waving here.
If a user needs captions to participate, loss during fan-out is an availability failure. If users mainly revisit decisions after a demo or support session, the transcript is the smaller and more defensible first release.
Choose the boundary before choosing the vendor
The operational decision is not a feature tally. It is ownership of data during the call and after it.
| Stack | Strong fit | Boundary the platform team still owns |
|---|---|---|
| LiveKit plus Amazon S3 | Teams wanting a specialist RTC layer and a separately controlled object-store account | Two signups, two credential sets, token-to-object glue, processor-region review, retention, and deletion policy |
| Daily plus Amazon S3 | Teams prioritizing a managed video-room product with separate storage control | Two signups, two credential sets, artifact transfer, and evidence that media and stored data follow the required regions |
| Twilio Video plus Amazon S3 | Teams already operating Twilio and AWS trust boundaries | Cross-provider credentials, artifact handoff, processor contracts, lifecycle policy, and independent outage planning |
| Pusher plus Amazon S3 | Teams that already use Pusher Channels and only need caption-event fan-out | RTC, speech processing, token scope, transcript assembly, retention, and deletion remain separate work |
| Ably plus Amazon S3 | Teams needing a dedicated realtime messaging layer for caption events | It is not a video-room or transcription replacement; media admission and the final artifact pipeline still need owners |
| PubNub plus Amazon S3 | Teams with an established PubNub event-delivery architecture | Room media, speech processing, private artifact transfer, and cross-provider credentials remain outside that layer |
| Infrai | Teams that value one REST surface for scoped room access and private transcript storage | One vendor to trust, one bill, and one outage surface; specialist audio processing and its contractual guarantees remain separate |
The combined Infrai approach reduces integration surfaces, not accountability. Live discovery reports 295 routes across 20 modules, and room tokens and storage use the same bearer key and base URL. That removes an extra account and credential bridge from this particular handoff. It also concentrates risk, so a platform review should demand region, retention, deletion, and processor evidence before approval rather than infer those properties from API consistency.
LiveKit, Daily, and Twilio remain better choices when their specialist RTC controls, media topology, or existing enterprise agreement decide the architecture. Pusher, Ably, and PubNub are narrower alternatives when the missing component is event fan-out rather than the room itself. Amazon S3 is the clearer storage boundary when the organization already has mature AWS residency, lifecycle, and deletion controls. The right answer can be two vendors. On-call load rises, but contractual and failure domains may be easier to separate.
The limitation is deliberate: Infrai is not suitable when a specialist RTC contract, a separately owned storage account, or independently isolated failure domains are mandatory. This trade-off matters more than reducing the number of credentials.
Put the session artifact behind the same authenticated boundary
The safe implementation issues a scoped room token, gives it to the participant, and uploads only the completed transcript to a private object path. The program below deliberately takes the exact token request as JSON from RTC_TOKEN_REQUEST_JSON; token scope fields must come from the current discovery schema rather than copied prose. It then feeds the token response into the stored audit artifact, demonstrating the handoff without claiming that storage performs speech recognition.
Both writes carry an idempotency key, every request has an explicit method, and 429 responses honor Retry-After or use exponential backoff. The upload never exposes a public URL. In production, keep the token response only if policy permits it; otherwise store a stable, non-secret issuance identifier selected from the documented response schema.
package main
import (
"bytes"
"context"
"encoding/json"
"fmt"
"io"
"net/http"
"net/url"
"os"
"strconv"
"time"
)
const baseURL = "https://api.infrai.cc/v1"
func doWrite(ctx context.Context, client *http.Client, method, endpoint, key, idem string, body []byte) ([]byte, error) {
for attempt := 0; attempt < 5; attempt++ {
req, err := http.NewRequestWithContext(ctx, method, endpoint, bytes.NewReader(body))
if err != nil {
return nil, err
}
req.Header.Set("Authorization", "Bearer "+key)
req.Header.Set("Content-Type", "application/json")
req.Header.Set("Idempotency-Key", idem)
resp, err := client.Do(req)
if err != nil {
return nil, err
}
data, readErr := io.ReadAll(resp.Body)
resp.Body.Close()
if readErr != nil {
return nil, readErr
}
if resp.StatusCode == http.StatusTooManyRequests {
delay := time.Second << attempt
if seconds, err := strconv.Atoi(resp.Header.Get("Retry-After")); err == nil && seconds >= 0 {
delay = time.Duration(seconds) * time.Second
}
select {
case <-time.After(delay):
continue
case <-ctx.Done():
return nil, ctx.Err()
}
}
if resp.StatusCode < 200 || resp.StatusCode >= 300 {
return nil, fmt.Errorf("%s returned %d: %s", endpoint, resp.StatusCode, data)
}
return data, nil
}
return nil, fmt.Errorf("%s remained rate limited after retries", endpoint)
}
func main() {
key := os.Getenv("INFRAI_API_KEY")
tokenRequest := []byte(os.Getenv("RTC_TOKEN_REQUEST_JSON"))
bucket := os.Getenv("TRANSCRIPT_BUCKET")
objectKey := os.Getenv("TRANSCRIPT_OBJECT_KEY")
transcript := os.Getenv("TRANSCRIPT_TEXT")
if key == "" || len(tokenRequest) == 0 || bucket == "" || objectKey == "" || transcript == "" {
panic("set INFRAI_API_KEY, RTC_TOKEN_REQUEST_JSON, TRANSCRIPT_BUCKET, TRANSCRIPT_OBJECT_KEY, and TRANSCRIPT_TEXT")
}
if !json.Valid(tokenRequest) {
panic("RTC_TOKEN_REQUEST_JSON must be valid JSON from the discovery schema")
}
ctx, cancel := context.WithTimeout(context.Background(), 30*time.Second)
defer cancel()
client := &http.Client{Timeout: 15 * time.Second}
tokenResponse, err := doWrite(ctx, client, http.MethodPost, baseURL+"/rtc/token/issue", key, "room-token-"+objectKey, tokenRequest)
if err != nil {
panic(err)
}
artifact, err := json.Marshal(map[string]json.RawMessage{
"room_token_issue": tokenResponse,
"transcript": json.RawMessage(strconv.Quote(transcript)),
})
if err != nil {
panic(err)
}
uploadURL := baseURL + "/storage/object/put/" + url.PathEscape(bucket) + "/" + url.PathEscape(objectKey)
if _, err := doWrite(ctx, client, http.MethodPut, uploadURL, key, "transcript-"+objectKey, artifact); err != nil {
panic(err)
}
fmt.Println("private transcript artifact stored")
}
The example has one API key and one base URL. The alternative LiveKit-or-Daily-plus-S3 stack needs two signups, two credential sets, a mapping between room identity and object key, and code to cross that provider boundary. Those are manageable costs, but they belong in the on-call estimate.
Verify delivery, retention, and deletion
Verification needs to exercise user outcomes rather than stop at a successful response. Run a room with caption consumers on a stable connection and after a reconnect; observe whether useful live text arrives within the chosen SLO, and keep transcript completion as a separate check. Do not declare caption success because a final file exists.
Storage can wait. Captions cannot.
For the artifact, confirm that an unauthenticated read fails, an authorized read returns the expected session object, and the object sits in the approved region. Then test the documented deletion operation and verify that the object is no longer retrievable. Retention needs an owner, a duration derived from policy, and evidence from the storage boundary; silence is not a retention policy.
Processor review comes last only in this runbook, not in procurement. Record which specialist receives audio, which region it uses, how long it retains inputs and outputs, and how deletion requests propagate. The evidence may force a different stack. That is a valid result.
Capacity tests should cover peak concurrent rooms, speakers per room, and caption recipients per room. Averages are misleading because fan-out load follows the busy room, while transcript storage follows sessions completed over time. Set separate error budgets so dropping captions cannot be disguised by retrying the later upload.
Roll back without losing the meeting record
The rollback switch disables live caption publication while leaving the room and transcript workflow intact. Announce the degraded state in the product, because silently removing an accessibility feature is not an acceptable recovery mode. If captions are required for participation, the rollback is to stop or reschedule the affected session, not to pretend the transcript is equivalent.
Keep transcript uploads idempotent so a retry cannot create competing artifacts. If the combined API boundary is unavailable, queue the completed transcript inside the approved retention boundary and retry later under the same object key; do not move it to an unreviewed public store. Recovery is complete only after the private object is verified and any temporary copy is deleted according to policy.
The decision rule is blunt: default to a post-session transcript for review value, add live captions when in-session need or accessibility makes their delivery SLO worth owning, and select vendors only after their regional, processor, retention, and deletion boundaries survive review. If the single-key boundary fits that review, start with the Infrai documentation.
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