Move AI from vision to measurable results.
ReKnew has delivered data platform modernization, self-service analytics programs, and driven $60M+ in annual benefit through AI and ML optimization. And we're just getting started.
The longer-term measure is how well your organization performs after we are no longer in the room. ReKnew partners with experienced teams to make that transition practical and sustainable.
Three programs, built to work together
ReKnew works across data, AI, and business transformation simultaneously because progress in one area depends on the others.
Modern Data Transformation
Trusted, AI-ready data foundations. Cloud platforms, pipelines, governance, and semantic layers.
AI and Agentic Transformation
AI agents and GenAI applications that automate complex workflows and run reliably in production.
Business AI Transformation
Aligning AI to business outcomes, redesigning workflows, and building organizational capability to sustain it.
The data foundation enterprise AI depends on
We build and modernize the cloud data platforms, pipelines, and governance functions that make enterprise data trustworthy and AI-ready, with experience delivering this in some of the most complex regulated environments in financial services.
Cloud data platform
Modern data lakes and warehouses on Snowflake, Databricks, and AWS, built for AI consumption.
Data governance
and quality
Lineage, quality controls, and compliance frameworks that meet regulatory standards.
Semantic layer and data products
Self-service data products and BI infrastructure that give teams consistent, trusted access.
DataOps and pipelines
Automated, monitored pipelines built to scale reliably as data environments grow.
Data foundations built for AI success
Established data models and pipelines to deliver reliable data at scale.
Context Engineering: from data platform to AI that performs
ReKnew's proprietary Context Engineering methodology gives AI agents the knowledge structures and operational controls they need to understand enterprise contextand execute workflows reliably.
Agentic AI and automation
Teams build proof of concepts without infrastructure to support them
GenAI applications
Production-ready applications for document processing, decision support, and customer-facing automation.
In production faster
AI solutions built on modern enterprise data principles delivered at scale.
Context and knowledge architecture
We architect the infrastructure and governance needed
AI platform and AIOps
Model governance, observability, and guardrails to run AI responsibly at scale.
Preparing the organization to work alongside AI
ReKnew's Adaptive Enablement practice addresses the organizational side of AI adoption: workflow redesign, team upskilling, and change management. This is where big wins can be found.
AI strategy and roadmap
Business-aligned strategy, use case identification, and a phased roadmap tied to operational outcomes.
Human-AI workflow design
Assessment and redesign of workflows around human-AI collaboration to improve efficiency and reduce risk.
AI fluency and upskilling
Programs that build data literacy and AI capability across business, operations, and technology teams.
Change management
Program governance, stakeholder alignment, and execution discipline for complex transformation initiatives.
Scaled AI workflows in production
Faster decisions, lower infrastructure costs, AI-fluency built in.
We meet you
where you are
Four engagement models depending on where your organization is in the journey.
01
Strategy refinement
Sharpen your AI, data, or talent strategy and define the priorities that matter most.
02
7-Point Assessment
A structured readiness evaluation across seven dimensions, resulting in a prioritized remediation plan.
03
Engineering support
ReKnew practitioners embedded alongside your team, from prototype through production.
04
Starter packs and accelerators
Pre-built frameworks and solutions that reduce time to value on common use cases.
Delivered at scale,
in complex environments
Progress that is visible and defensible AI initiatives in regulated environments must demonstrate measurable improvement while maintaining control. We define and track success the same way you do, with real business impact.
Top 20 US bank
$200M business case delivered on a modern data platform, including Snowflake migration and enterprise semantic layer.
Top 5 commercial credit company
Compliant data platform ingesting 60% of enterprise data, with self-service analytics for 200+ partners.
Top 20 US bank
$60M in annual benefit through AI/ML modernization across contact centers and digital channels.
Clear scope and proven outcomes that deliver real business impact.
Let’s start with a governed, real-world use case
Every engagement begins with a contained opportunity aligned to business value and regulatory boundaries..
