engineering · 1 min read
Streaming Architecture for LLM-Powered Apps
End-to-end streaming requires server, client and intermediaries to all behave. Here is the architecture Bhogar AI uses for sub-second perceived latency.
BABhogar AI TeamProduct & Engineering
Streaming is what makes AI feel fast. Implementing it end-to-end requires care: every hop (CDN, proxy, gateway, app, browser) has to play nicely.
Why it matters
Common failure modes: middleware buffers, connection limits, lost cancellations. The architecture has to anticipate each.
How Bhogar AI approaches it
Bhogar AI ships a streaming reference architecture: HTTP/2 throughout, SSE for one-way, WebSocket for bi-directional, cancellation propagated to upstream, no buffering middleware.
- HTTP/2 end-to-end with SSE / WebSocket
- Cancellation propagated upstream
- No buffering middleware
- Per-token telemetry without latency cost
- Compatible with major CDNs
What you get
Streaming AI features that match direct-API latency from the user's perspective.