What's included
Reduction in
manual workflow load
Data, Integration & Cloud
Turn Enterprise Data Into a Connected, AI-Ready Foundation.
Connect the data, applications, APIs, events, and cloud environments that power the business — so information moves with context, systems work together, and AI operates on trusted enterprise foundations. We modernize data architecture, engineer enterprise integrations, build API and event-driven connectivity, and create secure cloud foundations for applications, analytics, automation, and AI.
AI Is Raising the Cost of Disconnected Data and Architecture.
Most enterprises do not have a data shortage. They have a context, connectivity, trust, and operating-model problem.
Critical information is scattered across systems of record, SaaS applications, APIs, and cloud environments — producing duplicated data, brittle integration, and a foundation that’s harder to govern as AI expands.
Connect
Connect systems, applications, partners, data, and events.
Trust
Make data discoverable, governed, and usable in context.
Activate
Move data into applications, workflows, decisions, and AI.
Optimize
Place workloads where security, performance, and economics fit.
Build the Foundation That Applications, Operations, Analytics, and AI Can Share.
Six connected capabilities, designed to work as one foundation rather than six separate services.
Modern Data Architecture
Domain-aware foundations connecting operational, analytical, and document data.
Data Engineering
Batch, streaming, and orchestration pipelines with restart-safe processing.
Enterprise Integration
Connect core systems, SaaS, and partners with the right pattern.
API & Event Architecture
Governed APIs and event contracts, reusable by apps and AI agents.
Cloud Architecture & Modernization
Modernize cloud, hybrid, and multi-environment architecture around workload needs.
Cloud Platform & DevSecOps
Standardized infrastructure, CI/CD, and controls for consistent deployment.
Connect the Enterprise. Don't Replace It All.
Tech Tammina works within your architecture — connecting workflow platforms, cloud services, enterprise applications, and industry systems.
AWS
Cloud application and AI architecture using storage, databases, and container services.
- Object storage & managed databases
- Container platforms
- Security & observability
Microsoft Cloud & Enterprise Ecosystem
Integration with Microsoft enterprise services and cloud environments where appropriate.
- Identity & collaboration
- Content & data services
- Application services
Appian • Mendix • Camunda
Connect process and application platforms to enterprise data, APIs, and events.
- Systems of record & APIs
- Documents & events
- Cloud services
Enterprise Systems
Integration patterns for SAP, Oracle, PeopleSoft, Salesforce, Dynamics, and partner APIs.
- SAP, Oracle & PeopleSoft
- Salesforce & Dynamics
- AMS/BMS & partner APIs
How We Build the Foundation.
A managed-service relationship should have a visible operating lifecycle, not an indefinite steady-state queue.
Modernize Data Architecture
Design domain-aware foundations that preserve ownership and meaning.
Engineer Enterprise Integrations
Connect core systems, SaaS, and partners with the right pattern.
Build API & Event-Driven Connectivity
Turn capabilities into reusable interfaces for apps and AI.
Create Secure Cloud Foundations
Place workloads where performance, security, and economics align.
One Enterprise. Multiple Ways Information Has to Move.
A mature integration architecture doesn’t force every workload through the same pattern.
Real-Time & Synchronous
- Synchronous APIs — for request-response interactions needing an immediate result
- Events & Streaming — for near-real-time change propagation and decoupled processing
Scheduled & Long-Running
- Asynchronous Work — for long-running document, AI, and batch processes
- Batch & File — for scheduled files, bulk exchange, and legacy interfaces
Access & Continuity
- Data Access — for governed analytical and operational consumption via data products
- Human/Fallback Paths — for partner or legacy ecosystems where APIs are incomplete
Connected Architecture Around Real Business Work.
The strongest proof is not a technology list — it’s an operating process that becomes possible when systems, data, and cloud services work together.
Renewal Intelligence Platform
Insurance . AI + Cloud Architecture
An asynchronous AWS architecture connecting document storage, OCR, AI extraction, and review.
Flow: Upload → Extract → Normalize → Review → Generate
Connected Order Operations
Manufacturing . Enterprise Integration
Real-time APIs connecting order capture, SAP and pricing data, approvals, and dispatch.
Flow: Order → Validate → Approve → Dispatch → Track
Connected Vendor Operations
Manufacturing . Data + Partner Ecosystem
A vendor platform connecting SAP S/4HANA, SharePoint, shipments, and purchase orders.
Flow: Onboard → Transact → Integrate → Track → Analyze
Real-Time Risk & Fraud Signals
Financial Services . Event-Driven Data
Streaming architecture bringing transaction events, scoring, and case workflows together.
Flow: Event → Enrich → Score → Decide → Alert/Act
Integrated Digital Logistics Ecosystem
Logistics . Integrated Operations
Connect GPS, ERP, warehouse, CRM, and customer portals across the delivery lifecycle.
Flow: Plan → Move → Track → Bill → Notify
AI Readiness Starts With Business Context, Not Model Selection.
Advanced AI and agents need trusted context, governed permissions, and approved ways to act.
Context
Organize entities, documents, and domain knowledge AI can understand.
Quality
Validate completeness, consistency, and freshness before AI relies on it.
Semantics
Shared metadata and business definitions so terms mean the same everywhere.
Access
Expose governed data through APIs, data products, and approved services.
Lineage
Know where data came from and what depends on it downstream.
Action
Connect AI to approved APIs and workflows for controlled execution.
Architecture Should Improve the Economics of Information and Compute.
Senior technology leaders and investors need to see more than migration activity. Specific baselines and targets are defined per engagement — public outcome metrics are used only after validation.
Integration Reuse
Data Reuse
Change Lead Time
Cloud Unit Economics
Resilience
AI Readiness
What Could the Business Do If Data Moved With Context?
A policy comparison that sees the latest customer and policy data. A vendor portal connected to finance and logistics. A fraud decision made inside the transaction. An AI agent that can use approved enterprise tools. A cloud platform that scales without losing control. Bring us the business flow and the enterprise environment — we’ll help shape the data, integration, API, event, and cloud architecture to connect it.
What clients say
Alex Rivera
The team didn’t just build an automation; they re-engineered our entire operations workflow. We’re moving twice as fast now.
Sarah Jenkins
“Finally, an automation partner who actually understands enterprise security requirements. No hand-waving, just solid execution.”
Michael Rodriguez
“The team understood our complex integration requirements and built something that just works. Worth every penny.”
Marcia Solis
They made sense of our complex requirements and produced a solution that just works. Couldn’t be happier with the value.
Adam Smith
They quickly grasped our complicated integration needs and delivered a solution that works flawlessly. Absolutely worth the investment.
FAQ
Common Questions About Data & Integration Use Cases
What is Data, Integration & Cloud at Tech Tammina?
Data, Integration & Cloud is Tech Tammina’s capability for connecting enterprise data, applications, APIs, events, and cloud platforms into a governed, AI-ready foundation. It covers data architecture, data engineering, enterprise integration, API and event design, and cloud modernization — designed so applications, analytics, and AI can share one trusted foundation.
How does Tech Tammina connect systems of record, connectivity, and AI into one architecture?
We design the foundation as interoperable capabilities — data products, APIs, events, integration services, cloud platforms, and governance — so information moves across operational and analytical boundaries without losing ownership or meaning, wrapped by a control plane covering identity, policy, lineage, and cost.
How do you approach data products and data governance?
We design data products around business ownership and federated governance, not central bottlenecks: domain ownership stays with the teams closest to the data, backed by catalog and metadata, quality contracts, lineage and impact analysis, and access and privacy controls tied to role, purpose, and sensitivity.
What integration architecture patterns do you use?
We treat APIs and events as managed products: versioned API products, business-event contracts, orchestration for multi-system processes, and adapters that isolate legacy or vendor complexity. Idempotency, deduplication, and dead-letter handling protect asynchronous flows, with observability and least-privilege security built in throughout.
How do you approach cloud architecture and workload placement?
Cloud strategy is workload strategy: we place applications, data, and processing across cloud, hybrid, and edge environments based on performance, security, sovereignty, and cost. This includes standardized landing zones, infrastructure as code, resilience and disaster recovery, observability, and FinOps for cost and utilization visibility.
What is an AI control plane, and do you provide one?
As AI scales across models, agents, and workloads, the architecture needs common controls for how intelligence accesses data, invokes tools, and consumes compute — covering model and service access, context access, tool access, routing and placement, observability, and governance. This is a control-plane approach, not a proprietary product.
Which platforms and enterprise systems do you integrate with?
Within your existing architecture, we connect AWS, Microsoft’s cloud and enterprise ecosystem, and process/application platforms including Appian, Mendix, and Camunda, along with enterprise systems such as SAP, Oracle, PeopleSoft, Salesforce, Dynamics, AMS/BMS platforms, and partner APIs — according to verified project context.
How does this connect to Tech Tammina's other capabilities?
Data, Integration & Cloud is the shared foundation: it gives AI & Intelligent Automation trusted context and governed actions, gives Digital Engineering the APIs and data products for connected applications, supports Quality Engineering’s validation across distributed systems, and gives Managed Services the platform to operate after launch.