Data & Analytics

Your data team is spending 80% of their time moving data. Let's fix that.

Blissy AI builds AI systems for data and analytics teams — automated pipelines, natural language BI, anomaly detection, and intelligent reporting. Less plumbing. More insight.

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99.7%
Pipeline uptime (from 94.2%)
80%
Fewer on-call incidents
15%
Analyst time on prep (from 60%)
Sound Familiar?
Challenges we hear from Data & Analytics teams
We've built for this exact problem set. Here's what we typically hear before we start working together.
Your analysts spend most of their time on data prep, not analysis
ETL pipelines break. Schemas change. Someone is always cleaning something. The actual insight generation is a fraction of the week.
Business teams can't self-serve data — they always need a ticket
Every ad-hoc question creates a request. Every request takes 3 days. Decisions wait.
Anomalies in your data are discovered after the damage is done
A spike in churn, a drop in conversion, a pricing error in the feed — you see it in the weekly report, not in real time.
Your BI dashboards are built but nobody uses them
The dashboard was right at launch. Now it's stale, nobody trusts it, and every meeting still starts with a data pull.
Live Builds
What we've built for Data & Analytics
Every case below is live in production. IP fully transferred to the client on delivery. We don't retain access or use your data for model training.
Pipeline Automation11.1
Self-Healing Data Pipelines — Zero-Touch Data Operations
A data-heavy SaaS company had 40+ data pipelines maintained manually by a 5-person team. Schema changes downstream broke things weekly. On-call rotations were needed to handle pipeline failures. We built a self-monitoring pipeline infrastructure with AI-driven failure detection, auto-recovery for common failure patterns, schema drift alerts, and a natural language query interface so analysts could ask questions without writing SQL.
Outcome: Pipeline uptime: 94.2% → 99.7%. On-call incidents reduced 80%. Analyst time on data prep dropped from 60% to 15% of the week.
99.7%
Pipeline uptime (from 94.2%)
80%
Fewer on-call incidents
15%
Analyst time on prep (from 60%)
Self-healing pipelinesSchema monitoringNL queryingAuto-recovery
Natural Language BI11.2
NL BI — Every Business User Gets a Data Analyst
A retail analytics team was fielding 30+ ad-hoc data requests per week from business stakeholders. Each took 1-3 days. Decisions were delayed. We built a natural language BI layer on top of their data warehouse that lets any business user ask questions in plain English and receive accurate, chart-ready answers in seconds — with source citations and confidence levels.
Outcome: Ad-hoc request volume to data team dropped 78%. Business team decision speed improved measurably. Analyst team redeployed to strategic modelling work.
78%
Ad-hoc request reduction
Seconds
Query response time
0 SQL
Required from business users
NL to SQLData warehouseChart generationSource citation

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Other industries we build for
Digital Marketing →Manufacturing →FMCG & Distribution →Logistics →Retail & D2C →Hospitality →Agriculture →Education & Training →HR & People Ops →Legal & IP →