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Data Engineering

Real-Time Data Pipelines

Streaming analytics, event processing, and voice & audio pipelines — from ingest to insight with low latency and production-grade reliability.

Streaming Platforms

Move data as it happens

Event Streaming

Kafka, Pulsar, and cloud streaming buses with schema registries, consumer groups, and exactly-once processing where it matters.

Stream Processing

Flink, Spark Streaming, and custom workers for aggregations, joins, fraud scoring, and near-real-time feature pipelines.

Observability & Ops

Lag monitoring, DLQs, replay tooling, and SLO-backed alerting so pipelines degrade gracefully under load.

Voice & Audio

Voice and audio pipelines included

We design end-to-end audio systems for transcription, real-time voice agents, call analytics, and media processing — not just tabular event streams.

Voice Pipelines

Capture, stream, and process live voice with low-latency STT, diarization, and downstream NLU for support agents, IVR, and voice bots.

  • WebRTC / SIP ingest and media servers
  • Streaming speech-to-text with partial results
  • Speaker diarization and call summarization
  • Real-time agent assist and compliance redaction

Audio Pipelines

Batch and streaming audio processing for podcasts, meetings, media libraries, and quality monitoring — with storage, encoding, and enrichment stages.

  • Ingest, transcoding, and adaptive bitrate packaging
  • Noise reduction and audio quality scoring
  • Embedding & search over spoken content
  • Archival storage with retention policies

Common use cases

Fraud & Risk

Score transactions and sessions in milliseconds from streaming signals.

Product Analytics

Real-time funnels, feature flags, and user behavior pipelines.

Contact Centers

Live transcription, coaching, and QA on voice channels.

Media Platforms

Audio ingest, processing, and searchable content libraries.

Technologies

KafkaFlinkSparkPulsarRedis StreamsWebRTCWhisperDeepgramFFmpegTimescaleDBClickHouseAWS Kinesis

Need a real-time or voice pipeline?

Share your latency targets, data sources, and audio requirements — we'll propose an architecture.

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