Insights · Topic
Delivery and market
Forward-deployed delivery and the operating context around Indian systems. 10 guides, plus related customer work and papers.
About this topic
These articles describe how BluePi works and the market it works in: forward-deployed engineering, the first 90 days of a use case, and the operating realities of Indian mid-market businesses adopting data and AI systems.
They are useful before an engagement, when a team is deciding what a first use case should be and what a credible delivery partner should be expected to do.
Technical guides
Every guide in this topic, including the articles featured on the insights index.
Building an account-intelligence workbench for controlled operations
A bounded implementation record for a workbench that connects discovery, account memory, review, cost control, and export.
An AI-native SDLC playbook for enterprise engineering
Adapt planning, design, build, test, release, and maintenance practices without removing human accountability.
How client and delivery teams share ownership
A written split keeps delivery honest: the client owns decisions, data, and operations; the delivery team owns engineering, verification, and transfer.
What a production handover should contain
A handover checklist in three bundles: decisions, operating equipment, and open risks. The transfer is complete when the receiving team closes an incident alone.
Defining a baseline and target for a first deployment
Measure the current process, set a target with a period, and agree acceptance rules in writing before build starts. Three anti-patterns to avoid.
How to select the first production workflow
Score candidate workflows on decision frequency, data readiness, ownership, blast radius, and measurable result before a single build hour is spent.
What is forward-deployed engineering and when should you use it?
Forward-deployed engineering puts a small team inside one operating problem from framing through production release and ownership transfer.
Cloud Run GPUs: serve a model without running a cluster
Cloud Run GPU services give NVIDIA L4 acceleration with scale-to-zero billing. Configuration limits, the instance-based cost model, and when serverless GPUs beat a cluster.
Star and snowflake schemas: choose the model from the analytical use
Compare star and snowflake dimensional schemas by usability, governance, change, performance, and operating cost.
A practical digital-systems agenda for India's mid-market
Digitization drives India's economic growth by lowering the cost of transacting, verifying, and distributing. Aadhaar and UPI compressed identity and payment friction, GST formalized reporting, and cheap data moved first-time users onto digital rails. For mid-market firms the practical effect is operational: demand signals, logistics, and payments now arrive as data, so value comes from systems that act on that data.
Customer work and research
Customer work and technical guides on this topic.
A QSR executive cockpit reduced KPI latency from 30 minutes to about one minute
A multi-brand QSR operator relied on manual spreadsheet pivots and distributed reports for daily measures. BluePi built streaming and batch data paths, Snowflake reconciliation, Java APIs, and a custom React cockpit that brought KPI visibility to approximately one-minute latency.
Yum Brands put sales-driver and what-if analysis into daily operating decisions
Yum Brands needed to understand changing sales drivers and test response scenarios during a period of rapid demand disruption. BluePi built a cloud analytical path with SQL Server, Amazon EC2, Amazon EMR, and Power BI and released it in a matter of weeks.
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