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Enterprise Data Engineering · Databricks · AI

Engineering tomorrow's intelligent enterprises.

Modern data platforms. Production-grade AI. Karsient modernizes legacy data estates onto the Lakehouse, engineers governed cloud data platforms, and builds AI that runs in production — with measurable gains in performance, cost, and time-to-insight.

Databricks MigrationLegacy ModernizationData EngineeringAI & GenAICloud PlatformsPerformance & Cost Optimization

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What we do

A full data-to-AI capability, under one roof

Six core specialisms that cover the full lifecycle — from raw data to governed platforms to production AI.

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01

AI & Generative AI

Enterprise AI solutions, copilots, RAG, and intelligent automation.

  • LLM & generative AI applications
  • Retrieval-augmented generation (RAG)
  • Copilots & intelligent automation
  • Model monitoring & evaluation
GPTClaudeRAGLangChain
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02

Data Engineering

Modern data lakes, ETL/ELT pipelines, Databricks and Spark.

  • Lakehouse & ETL/ELT pipeline design
  • Databricks & Apache Spark delivery
  • Data quality & observability
  • Schema & contract management
DatabricksApache Spark
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03

Cloud Modernization

Azure, AWS and hybrid cloud migration with secure architectures.

  • Migration assessment & roadmap
  • Secure, well-architected landing zones
  • Cost modelling & FinOps
  • Post-migration validation
Microsoft AzureAWS
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04

Analytics & BI

Power BI dashboards, semantic models and executive reporting.

  • Executive & operational dashboards
  • Self-serve semantic models
  • Power BI & Microsoft Fabric delivery
  • Adoption & enablement training
Power BIMicrosoft Fabric
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05

Data Platform

Lakehouse architecture, governance and scalable platforms.

  • Lakehouse & warehouse architecture
  • Transformation pipelines with dbt
  • Cataloguing, lineage & governance
  • Scalable, cost-tuned platforms
Snowflakedbt
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06

Managed Services

24×7 monitoring, optimization and enterprise support.

  • 24/7 platform monitoring & support
  • SLA-backed incident response
  • Continuous cost & performance tuning
  • Quarterly roadmap reviews
Azure MonitorDatabricksCloud Operations
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Platform architecture

A reference architecture for the modern data & AI estate

Sources through to business outcomes — the same architectural pattern we tailor to every migration and platform build.

SAP

Sources

  • ERP / CRM
  • Databases
  • Files & APIs
  • Streaming Events
Apache Airflow

Ingestion

  • Auto Loader
  • CDC
  • Batch & Streaming
  • API Gateways
Databricks

Lakehouse

  • Bronze
  • Silver
  • Gold
  • Delta Lake
Unity Catalog

Governance

  • Unity Catalog
  • Access Policies
  • Lineage
  • Data Quality
dbt

Engineering

  • dbt Models
  • Workflows
  • CI/CD
  • Infra as Code
Power BI

Analytics & AI

  • SQL & BI
  • ML / MLOps
  • GenAI & Agents
  • APIs
Security & IAM
Cost & FinOps
Data Contracts
Observability

Live data flow · sources to outcomes

Business Outcomes: faster time-to-insight · lower platform cost · governed, trusted data · production AI

Products

Not just consulting — a toolkit for the migration itself

ShiftIQ, CodeShift, RevoCode, and Veriq: the four products behind every Karsient-led modernization, available standalone or bundled with our delivery team.

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karsient-shiftiq — dependency graphLEGACY_PROC.SQLCREATE OR REPLACE PROCEDURE calc_customer_ltv(cust_id NUMBER)IS v_total NUMBER := 0;BEGIN SELECT SUM(amount) INTO v_total FROM orders WHERE customer_id = cust_id; RETURN v_total;END;-- complexity: high, 3 refsBusiness rule detected: LTV calcDEPENDENCY GRAPHorderscustomerscalc_ltv()ltv_calcdim_customerrpt_ltv
AI-Powered Legacy Modernization Intelligence

Karsient ShiftIQ

Understand Legacy. Plan the Shift. Modernize With Intelligence.

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karsient-codeshift — side-by-side diffSOURCE SQL (Oracle)SELECT customer_id, SUM(amount) AS totalFROM orders oJOIN customers c ON o.cust_id = c.idWHERE o.status = 'PAID'GROUP BY customer_idDATABRICKS · PYSPARKdf = (spark.table("orders") .join(customers, "cust_id") .filter(col("status")=="PAID") .groupBy("customer_id") .agg(sum("amount")))98% confidence
AI-Powered Code Transformation & Migration

Karsient CodeShift

Transform Legacy Code. Accelerate Modernization.

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karsient-revocode — optimization scorecardMaintainability82/100Technical Debt-34%Query Perf.+41%Cost Savings$18K/moBEFORE — nested subquerySELECT o.id, c.nameFROM orders oJOIN ( SELECT * FROM customers) c ON o.cid=c.idAFTER — flattened joinSELECT o.id, c.nameFROM orders oJOIN customers c ON o.cid = c.id-- pruned unused columnsRECOMMENDED OPTIMIZATIONSEnable liquid clustering on gold.sales_factHigh impactDeprecate unused bronze.legacy_staging jobLow impactRight-size cluster for nightly batch jobMedium impact
AI-Powered Code Modernization & Optimization Platform

Karsient RevoCode

Modernize Today. Continuously Engineer Tomorrow.

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karsient-veriq — command centerDATA TRUST SCORE91.4Active Incidents6Quarantined312Auto-Resolved84%Avg. Resolution11mTRUSTPASSWARNQUARANTINEREMEDIATEREVALIDATERELEASESMART QUARANTINE — ROOT CAUSE GROUPEDcustomers.date_of_birth — format anomaly1,204 recordsHigh impactorders.customer_id — referential integrity88 recordsMedium impactgold.revenue_kpi — aggregation drift3 datasetsHigh impactsilver.shipments — duplicate keys412 recordsLow impact
AI-Native Data Trust & Control Plane

Karsient Veriq

From Data Quality to Data Trust.

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Our stack

Technology Platforms

Enterprise technologies we use to build secure, scalable and AI-ready solutions.

Databricks
Databricks
Microsoft Azure
Microsoft Azure
AWS
AWS
Google Cloud
Google Cloud
Microsoft Fabric
Microsoft Fabric
Snowflake
Snowflake
Apache Spark
Apache Spark
Apache Kafka
Apache Kafka
dbt
dbt
Power BI
Power BI
Python
Python
SQL
SQL
Microsoft SQL Server
Microsoft SQL Server
Oracle
Oracle
Apache Iceberg
Apache Iceberg
Delta Lake
Delta Lake
Unity Catalog
Unity Catalog
Apache Airflow
Apache Airflow
LangChain
LangChain
Informatica
Informatica
SAP
SAP
Salesforce
Salesforce
MongoDB
MongoDB
Terraform
Terraform

What we build with

Platform Capabilities

The core stack behind every engagement — engineering, cloud, AI, and analytics working as one.

Databricks

Data Engineering

  • DatabricksDatabricks
  • Apache SparkApache Spark
  • Delta LakeDelta Lake
Microsoft Azure

Cloud

  • Microsoft AzureMicrosoft Azure
  • AWSAWS
  • TerraformTerraform
Generative AI

AI

  • OpenAIOpenAI
  • ClaudeClaude
  • Vector SearchVector Search
Power BI

Analytics

  • Power BIPower BI
  • SQLSQL
  • Semantic ModelsSemantic Models

Why Karsient

A technical partner, not just an advisor

We are engineers first — the same people who design your architecture also help build and operate it.

Platform-agnostic expertise

Deep experience across Databricks, AWS, Azure, and GCP — we recommend what fits, not what's familiar.

Engineers, not just advisors

Our consultants write and ship production code alongside your team, not just slide decks.

Governance from day one

Security, lineage, and compliance are built into every architecture, not bolted on later.

Outcome-based partnership

We measure success in decisions enabled and cost removed, not hours billed.

Industry expertise

Built for regulated, data-intensive industries

Every industry has its own data gravity and compliance load. We bring pattern-matched experience, not generic playbooks.

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Proof, not promises

Recent client success stories

A sample of engagements across our core industries. Full case studies available on request.

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Projects delivered

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Consultants & engineers

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Client satisfaction

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Industries served

Client voices

What partners say about working with us

Karsient rebuilt our data platform in months, not years, and our analysts finally trust the numbers.

VP of Data, Enterprise Client · Financial Services

Their team felt like an extension of ours — technically sharp and genuinely invested in the outcome.

Director of Engineering · Retail Client

The governance framework they implemented turned audits from a scramble into a formality.

Head of Compliance · Healthcare Client

How we work

A disciplined, ten-stage delivery methodology

Every engagement — whether a two-week assessment or a year-long platform build — follows the same disciplined path, from discovery through to running it for you.

01

Discovery

Understand business goals, current systems, and constraints before proposing anything.

02

Assessment

Inventory databases, tables, pipelines, workloads, dependencies and usage across the estate.

03

Architecture

Design the target Databricks Lakehouse architecture, Unity Catalog, and governance model.

04

Design

Define detailed technical design — data models, pipeline patterns, and platform standards.

05

Migration

Move data, SQL, transformations and pipelines in planned, testable phases.

06

Engineering

Build and re-engineer pipelines, jobs, and integrations on the target platform.

07

Validation

Compare record counts, aggregations, business rules, data quality and performance against source.

08

Optimization

Tune file sizes, partitioning/clustering, SQL, compute, and Delta table configuration.

09

Deployment

Move production traffic with a rollback plan and minimal disruption to downstream consumers.

10

Operate

Hand over with documentation and training, or continue under a managed-services partnership.

Let's build the future together

Ready to turn your data into a decision engine?

Tell us about your platform, your team, and your timeline — we'll follow up within one business day with a plan.