What does Kelriva AI build in Data Analytics & Intelligence?+
Kelriva AI designs and delivers AI-powered data pipelines, cloud data warehouses, real-time BI dashboards, and predictive analytics systems for enterprise clients. We take raw, siloed data from across your business and transform it into a unified intelligence layer that powers faster and more accurate decisions. Our clients typically see data pipeline build times reduced by 60–70% and reporting turnaround cut from days to real time.
What is a data pipeline and why do enterprises need one?+
A data pipeline is an automated system that continuously collects, transforms, validates, and loads data from multiple source systems into a central location for analysis. Without a pipeline, businesses rely on manual data exports, spreadsheets, and disconnected reports that are always out of date. A well-built AI-powered pipeline gives you a single source of truth that updates in real time and enables your analysts to focus on insight rather than data wrangling.
What BI tools and platforms does Kelriva AI work with?+
We build on Tableau, Power BI, Looker, Metabase, and Apache Superset depending on your stack and requirements. For data warehousing we use Amazon Redshift, Google BigQuery, Snowflake, and Databricks. For pipeline orchestration we use Apache Airflow and DBT. We are cloud-agnostic and choose the right tool for your specific data volume, team skills, and budget.
Can you build ESG data analytics and sustainability reporting systems?+
Yes. ESG data analytics is one of our specialist verticals. We build systems that aggregate ESG data from multiple internal and external sources, calculate metrics against TCFD, GRI, CSRD, and SFDR reporting frameworks, and produce audit-ready dashboards for sustainability teams and boards. Our ESG systems include automated data sourcing via LLM-powered web retrieval, scoring engines, and transparent citation trails for regulatory compliance.
What is predictive analytics and how does it help enterprise businesses?+
Predictive analytics uses statistical models and machine learning to forecast future outcomes based on historical data. For enterprise clients this means predicting customer churn before it happens, forecasting demand to optimise inventory, identifying credit risk earlier in the underwriting process, or detecting compliance anomalies before they become regulatory issues. Kelriva AI builds predictive models that are production-ready, explainable, and integrated directly into your existing reporting infrastructure.
How long does a data analytics project take?+
A data pipeline and BI dashboard engagement typically takes 4–8 weeks from discovery to delivery depending on data source complexity and integration requirements. Predictive analytics or ML model builds may take 6–10 weeks. All engagements are fixed-fee with clearly defined deliverables agreed upfront — no day rates, no scope creep, no surprise invoices.
What industries does Kelriva AI serve with data analytics?+
Our primary verticals for Data Analytics & Intelligence are Fintech, Finance, ESG and sustainability, and Corporate Coaching. We build data systems for financial services firms needing real-time risk and portfolio analytics, ESG organisations needing automated sustainability reporting, and coaching businesses needing to analyse client outcomes at scale. We serve clients across the UK and Europe from our London base.
Do you offer ongoing support after delivering a data analytics system?+
Yes. All engagements include a handover period with full documentation and team training. We also offer optional managed support packages for ongoing pipeline monitoring, model retraining as data patterns change, and dashboard evolution as business requirements develop. Support terms are agreed as a separate fixed-fee arrangement after initial delivery.