Data Solutions
Data infrastructure
that scales with your business
(What we do)
We design and engineer the data foundation that powers automation, AI, and business decisions - built to scale with your organization.
THE ARCHITECTURAL GAP
Is your infrastructure scaling with your business - or slowing it down?
What you can expect:
Kynera engineers production-grade data architecture. We rebuild your foundation to deliver the sub-second performance, absolute data integrity, and ultimate scalability required for enterprise AI and automation.
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DATA ARCHITECTURE TYPES
Scalable Frameworks for Modern Data Infrastructure
We engineer bespoke data platforms tailored to your operational scale, security requirements, and organizational maturity. Choose the foundational model that fits your business growth.
Cloud Data Platform
We design and deploy centralized cloud lakehouses with decoupled storage and compute. This architecture ensures your infrastructure instantly scales to handle any volume while dynamically optimizing cloud spend.
Hybrid Data Infrastructure
We build a secure, high-speed bridge between your on-premise hardware and scalable cloud environments. Sensitive core assets remain strictly protected inside your private network, while heavy analytics and AI scale in the cloud.
Decentralized Data Mesh
We eliminate the bottleneck of a single central data team. We transition your enterprise to a federated model where data is managed directly by business domains as an internal product, connected via a unified network.
SCOPE OF ENGAGEMENT
Flexible Engagement Models
Depending on your organization's data maturity, we can architect your entire ecosystem from scratch or execute a hyper-focused technical sprint.
01
Data Audit & Strategy
Structured inventory of data sources, formats, ownership, and quality gaps - producing a prioritized architecture strategy with clear sequencing and budget.
02
Data Architecture Design
End-to-end design of your data infrastructure - storage layers, integration points, warehouse or lakehouse selection, and scalability planning matched to your business requirements.
03
ETL / ELT Pipeline Engineering
Development of reliable data collection, transformation, and loading pipelines with orchestration, monitoring, and failure recovery.
04
Data Modernization & Migration
Migration of legacy systems, fragmented databases, and manual processes to a modern, scalable data stack - without disrupting ongoing operations.
05
Self-serve BI & Data Democratization
Setup of environments where business teams access and analyze data without queuing for analyst support - matched to your team's technical level and tooling.
06
Data Infrastructure Cost Optimization
Analysis of data infrastructure spend across cloud, licensing, and storage - identifying inefficiencies and restructuring for cost reduction without losing capability.
07
Data Governance & Quality Framework
Ownership structures, data catalogues, quality controls, and lineage tracking - making data auditable, trustworthy, and compliant.
AI & Automation Ready
Structured, governed data means every next layer - automation, intelligence, prediction - can be added without rebuilding the foundation.
Infrastructure That Scales
Architecture built on modern, open standards - handles data growth, new sources, and team expansion without full replacement cycles or vendor lock-in.
Decision Intelligence Ready
Clean, connected data unlocks predictive analytics and AI-powered decision systems - the direct path to your next strategic layer.
Reduced Infrastructure Costs
Optimized spend across cloud, licensing, and storage - typical outcome: up to 30–50% reduction without losing capability.
Operational Independence
Business teams access and analyze data without queuing for engineering support - self-serve capability built into the architecture from day one.
Unified Data Across the Organization
All systems connected through a single data layer - finance, operations, marketing, and sales working from the same source of truth.
Do we need a data warehouse if we're not a large company?
If you have more than one system generating business data - yes. The question is which architecture fits your scale and budget.
How does this connect to AI and automation?
Clean, governed data is the prerequisite for any AI or automation initiative. This is the foundation everything else runs on.
How much does cloud data infrastructure cost to run?
Depends on volume and architecture. A properly designed stack for mid-market typically runs $500-$3,000/month. We also optimize existing spend./
Do we need an internal data team to maintain it?
Not necessarily. We design for maintainability - and can provide ongoing support where needed.
We already have dashboards. Why do we need this?
Dashboards show what your data allows. If the underlying infrastructure is fragmented, your dashboards are only as reliable as your worst data source.
How long before we see results?
First usable outputs typically within 4-8 weeks. Full architecture deployment: 3-6 months.
Contact Us
Let's establish whether Kynera is the right fit for your organization
Email
hello@thekynera.com
Support
info@thekynera.com
Customer Service
Mon-Fri 10am-6pm
+1 (437) 476-6900
LinkedIn
@thekynera
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