BloomKloud AI lifts enterprises out of costly on-premise data silos and into the AWS cloud era — modernizing legacy Oracle, Teradata, SQL Server, and Hadoop environments into agentically governed Redshift, Snowflake, and Databricks platforms.
Deep cluster architecture expertise — WLM tuning, QMR governance, distribution and sort key optimization, concurrency scaling, and production monitoring at petabyte scale.
Full migration architecture from Redshift to Snowflake — IAM storage integration, PrivateLink, Secrets Manager, KMS encryption, and multi-stage Glue PySpark pipelines.
Lakehouse architecture with medallion design, Unity Catalog, Delta Lake, and AWS lakehouse integration — bridging the gap between cloud data warehouses and open lake formats.
Most enterprises are still running critical data workloads on aging on-premise infrastructure — Oracle Exadata, Teradata, Netezza, SQL Server, or Hadoop clusters that cost a fortune to maintain and can't scale to meet modern analytics demands. We fix that.
On-prem data warehouses require expensive hardware refreshes, Oracle/Teradata licensing fees, and dedicated DBA teams just to keep the lights on — with zero elasticity when demand spikes.
Legacy systems hit hard limits — fixed CPU, memory, and I/O capacity mean slow query times, long ETL windows, and frustrated business users waiting hours for reports.
Siloed on-prem databases, incompatible formats, and brittle point-to-point ETL pipelines make it nearly impossible to get a unified view of enterprise data in real time.
Legacy infrastructure was never designed for ML, NLP, or agentic AI. Without cloud-native data foundations, organizations are locked out of the intelligence layer entirely.
Full audit of existing on-prem landscape — schema profiling, data volume analysis, query workload assessment, dependency mapping, and TCO comparison vs. AWS cloud alternatives.
Move data from on-prem sources to AWS using AWS DMS, Direct Connect, Snowball Edge, or secure SFTP — landing as Parquet in S3 data lake with catalog registration in AWS Glue.
Convert legacy SQL dialects, stored procedures, and ETL logic to AWS-native equivalents — PySpark on Glue, Redshift-compatible SQL, and cloud-optimized schema designs.
Row-count reconciliation, data quality checks, parallel-run validation, and zero-downtime cutover with rollback plans — ensuring business continuity throughout the migration.
Post-migration tuning — WLM queues, distribution keys, sort keys, auto-scaling policies — followed by deploying agentic AI agents for continuous autonomous optimization.
End-to-end lift-and-shift and re-platform migrations from Oracle, Teradata, SQL Server, Netezza, and Hadoop to AWS — using DMS, SCT, Snowball Edge, and Direct Connect with zero-downtime cutover.
Design and deploy production-grade data warehouse architectures on Redshift, Snowflake, and Databricks — optimized for cost, performance, and governance at enterprise scale.
AWS Glue PySpark pipelines, incremental watermark-based loads, Parquet + Snappy on S3, parallel processing with ThreadPoolExecutor, and DMS/Kinesis streaming ingestion.
IAM, RBAC, SSO via Azure AD, Lake Formation RBAC, KMS encryption, VPC endpoints, Secrets Manager, and PII/PHI classification with dynamic masking for regulated industries.
WLM/QMR queue engineering, distribution and sort key analysis, query plan optimization, concurrency scaling governance, and stl_query / stl_wlm_query monitoring dashboards.
Terraform and CloudFormation templates for repeatable, version-controlled cloud data infrastructure — VPC configuration, security groups, cluster provisioning, and IAM role management.
BloomKloud AI's agentic platform orchestrates a multi-agent pipeline that continuously monitors, optimizes, and governs your cloud data warehouse — without manual intervention.
Built on the AI Data Warehouse Advisor framework, our agents collect system telemetry, analyze performance patterns, recommend architectural changes, and execute approved remediations autonomously.
10 years in AWS data modernization consulting across healthcare, financial services, energy, media, hospitality, and transportation — delivering cloud data solutions at Fortune 500 scale.
RedAI monitors your Redshift cluster 24/7, diagnoses performance bottlenecks across 18 known waste patterns, and generates approved fix SQL — autonomously. Built by a Redshift architect with 10 years of production cluster experience. For data engineering teams that are tired of guessing.
A cluster burning $200K/yr with 30% waste = $60K recoverable annually. RedAI Professional at $8K/mo pays for itself before the first invoice arrives. Every client has converted within 30 days of seeing their waste report.
Your team finds out about slow queries after the VP complains. By then the compute is burned and the meeting is already scheduled.
Reading stl_alert_event_log, tuning WLM service classes, diagnosing DISTKEY mismatches — this takes years of Redshift experience most orgs don't have.
35–60% of your Redshift bill is wasted. Finance sees it. Nobody knows why. No tool generates the fix. Until now.
RedAI runs a continuous five-stage pipeline across your cluster — every day, automatically — with your approval before any change executes.
Queries stl_query, stl_wlm_query, svv_table_info, stl_alert_event_log, CloudWatch on EventBridge schedule.
LLM interprets 18-pattern Redshift library against your telemetry — scoring by cost impact, fix complexity, confidence.
Outputs ranked JSON: finding + severity + fix SQL + estimated monthly savings. No guessing.
Slack message: Approve or Skip. Nothing runs without your sign-off. Full audit trail in S3 + CloudTrail.
Applies approved DDL via IAM least-privilege. Logs before/after metrics. Schedules 48hr performance check.
Built by someone who's spent 10 years in Redshift system tables — not a generic AI wrapper trained on Stack Overflow posts.
Ranks every query by estimated $/hr using actual execution time × your cluster's hourly rate. Exact cost per user, per queue, per table.
Detects ETL jobs crowding out BI in WLM service classes. Generates config changes that eliminate starvation without manual guesswork.
Identifies tables causing full-table scans or cross-node shuffles from wrong DISTSTYLE. ALTER TABLE fix SQL with savings estimate attached.
Flags sort keys that are unused, redundant, or misaligned with actual query patterns. Zone map effectiveness measured and reported.
Tracks which workloads trigger expensive burst scaling — and whether it's justified. Surfaces WLM changes that eliminate unnecessary events.
Zero autonomous DDL. Every fix gets Slack Approve/Skip. IAM least-privilege execution. S3 + CloudTrail audit. SOC 2 compliant from day one.
Start with a one-time audit. No contract. Every client has converted within 30 days of seeing their waste report.
Please reach out to us for pricing.
Every engagement is scoped to your cluster size, number of environments, and optimization goals. We'll build a plan that's ROI-justified before you sign anything.
Contact Us for Pricing →Stop leaving money on the table.
Book a 30-minute demo — we'll run a live scan and show you exactly what's costing you. Zero cost. Zero commitment.
At BloomKloud AI, we specialize in connecting businesses with skilled IT professionals to meet their unique staffing needs. Whether you're looking for permanent hires, contract staff, or temporary talent to power your cloud data modernization initiatives — we've got you covered across the United States and India.
Find the right talent for permanent roles — ensuring a perfect fit for both technical skills and company culture. We evaluate expertise across AWS, Redshift, Snowflake, Databricks, and data engineering disciplines.
Access skilled IT professionals for short-term projects, cloud migration sprints, seasonal demands, or specific data engineering initiatives — without the overhead of full-time hiring.
Evaluate candidates on a contract basis before committing to a permanent hiring decision. Reduce risk and ensure technical fit, cultural alignment, and team dynamics — before making a long-term investment.
Quickly fill temporary IT roles to maintain business continuity during cloud migrations, system upgrades, parental leave, or unexpected capacity gaps — without disruption to your data operations.
We've helped enterprises achieve their digital transformation and cloud data modernization goals — from on-prem legacy migrations to full agentic AI platforms.
We've placed skilled IT and data professionals in rewarding roles across healthcare, finance, energy, and media — fostering growth and long-term career development.
Our consulting and staffing engagements have enabled clients to stay ahead — deploying AWS-native architectures, agentic AI agents, and modern data governance frameworks.
Whether you're planning a warehouse migration, building agentic AI pipelines, or optimizing a production Redshift cluster — let's architect the right solution together.