Real-time data pipelines for decisions that cannot wait
We build streaming pipelines that capture events as they happen and deliver them to live dashboards, alerts and the applications that need them.
What we take on
- Use-case reviewWe confirm which decisions need live data and which are served well by batch, before building.
- Event streaming setupKafka, or a managed service such as Amazon Kinesis or Azure Event Hubs, set up and secured.
- Stream processingEvents filtered, joined and aggregated in flight with tools such as Flink or Spark Streaming.
- Live dashboards and alertsStreaming data delivered to the dashboards and alerts the right people see.
- Monitoring and recoveryLag, failures and replays watched and documented, so the pipeline can be trusted.
Streaming and batch pipelines in one design, run by one team.
Where this fits in your stack
Real-time Data Pipelines builds on our Data Engineering work and is done by the same team that covers the rest of the path.
When companies call us about real-time data
You notice: By the time our reports refresh, the moment to act has passed.
What we do: We stream the events that matter to a live view or an alert, and leave the rest on batch.
Discuss thisYou notice: We need to spot failed payments or stock-outs while they are happening.
What we do: We build alerts on the event stream, routed to the team that handles them.
Discuss thisYou notice: Our streaming setup works, but nobody trusts it after the last outage.
What we do: We review it, fix how it handles failures and replays, and add monitoring.
Discuss this
Where we do real-time data, by industry
What this service does in each sector, from that sector's page. Open yours to see the full picture.
All 8 real-time data use cases- Manufacturing & RetailMachine stoppages are logged by hand, if at all, so their causes are hard to trace.
- Transport & LogisticsGPS data is collected but never joined to trips, costs or delivery times.
- TelecomUsage and network event volumes outgrow the databases and batch jobs built for them.
- Media & EntertainmentPlayback problems show up on social media before the team sees them in data.
- BFSISuspicious transactions are reviewed days later, from batch reports.
- Travel & HospitalityLive availability and booking feeds for operations screens and alerts.
How an engagement starts
You see a written plan with scope, timeline and team before any work begins.
Step 1: Talk
A call with our engineers about your systems, your data and the decisions you need it for.
Step 2: Assess
We review your current setup and send a written plan with scope, timeline and team.
For streaming work, that review covers your event sources, volumes, how fresh the data needs to be and what happens downstream when it arrives.
Step 3: Build and run
We deliver the work with documentation, and can stay on to run and support it.
Common questions
Something else on your mind? Email info@analyca.in or book a consultation.
Do we need real-time data?
Which streaming tools do you use?
Can streaming data feed our existing dashboards?
How do we start working together on real-time data?
What you can hold us to
Companies we have delivered projects for:
A written plan before any work starts
After the first call we review your setup and send scope, timeline and team in writing.
Documentation with everything we deliver
Pipelines, databases, dashboards and deployments are handed over with documentation your own team can follow.
One team accountable for the result
The same engineers work across your databases, pipelines, dashboards and releases.
Book a consultation
Tell us what you are working on. An engineer from our team will get back to you to set up a call.