Modernize existing cloud. Know enterprise data. Ship AI with purpose.
Security and compliance built in.
TalentPros Hub helps leaders make confident decisions before funding complex cloud, data, AI, integration, and cybersecurity programs. We turn technical uncertainty into an executive roadmap, secure architecture, and phased delivery plan.
Services leaders can understand and engineering teams can execute.
Focused services for clients who need executive clarity, technical depth, and security discipline across cloud, infrastructure, integration, data, AI, and operations.
Cloud Modernization
Assess and modernize applications, databases, infrastructure, and operating models across AWS, Azure, and GCP.
Cloud strategy & advisory
App & database migration (RDS, Snowball)
Landing zones, IaC, DevOps, SRE foundations
FinOps & cost optimization
Infrastructure & Hybrid Networking
Design the network, segmentation, hybrid connectivity, and data center integration foundation needed for secure cloud adoption.
Cloud network design and segmentation
AWS Transit Gateway and Azure ExpressRoute
Zero-trust and semi-trust traffic review
Data center, VPN, DNS, firewall integration
Integration & Messaging
Connect internal platforms, external partners, files, APIs, events, and legacy systems using secure synchronous and asynchronous patterns.
A2A, API, event, and batch integration
File, SFTP, NDM, and MFT patterns
Internal and external partner connectivity
Queue, pub/sub, streaming, and workflow design
Data Strategy & Engineering Roadmap
Map fragmented sources, reports, KPIs, ownership, and MDM gaps into a practical platform and engineering roadmap.
Source, system, report and KPI discovery
MDM with owners, stewards, and domains
ETL/ELT to object storage, warehouse, lakehouse
Governed analytics with RBAC and ABAC
Cybersecurity & Compliance
Security architecture, control validation, privacy, GRC, and risk mitigation built into cloud, data, and AI decisions.
Security architecture review
Compliance validation: SOC 2, HIPAA, PCI
DevSecOps & cloud posture management
Risk mitigation playbooks
Managed Services & Global PODs
Dedicated delivery and operations PODs with named outcomes, weekly reporting, and senior oversight.
Cloud & data managed operations
Subcontracted global delivery PODs
SRE, observability & on-call
Continuous optimization & FinOps
Training & Enablement
Equip your teams to own what we build — cloud, data, AI, and security fluency that lasts.
Role-based curricula (eng, ops, security)
Hands-on labs & workshops
AWS / Azure / GCP certification prep
Internal champion programs
AI From Governed Data
Use clean, policy-governed data and documents to support analytics, ML, RAG, GenAI, and controlled agentic workflows.
LLM with RAG over governed content
LangChain, guardrails, citations, audit trails
Fraud, anomaly detection and prevention
Feature store, MLflow, ML and agentic AI
02 — AI Ecosystem
AI-Ready Data Ecosystem & Agentic RAG.
A practical blueprint for turning fragmented enterprise data into governed analytics, quality data products, feature pipelines, ML, and secured LLM decision support with RAG, LangChain-style orchestration, citations, guardrails, and auditable actions.
Sources
DBOperational databases
SaaSSaaS applications
StreamStreaming events
FilesFiles, reports & logs
Ingest
Batch / file ingestion
Fivetran · ADF · Glue · SFTP/MFT
Streaming ingestion
Kafka · Kinesis · Event Hub
Lakehouse
S3 / ADLSCloud Data Lake
DatabricksSpark & Delta Lake
SnowflakeGoverned Analytics
dbt / AirflowTransform & Orchestrate
Bronze · raw→Silver · cleansed→Gold · business data products
We start with source, system, report, KPI, owner, and steward discovery, then define the roadmap for resolving fragmented analytics, duplicate metrics, inconsistent reporting, and MDM gaps.
Source and report inventory
Analytics discrepancy and KPI rationalization
MDM domains, owners and stewards
Data strategy and engineering roadmap
Engineering Build
Trusted data platform and governed analytics
ETL/ELT pipelines land data into object storage, warehouse, and lakehouse layers where transformations, models, tests, data quality checks, and access controls create usable, governed business data.
Object storage, warehouse and lakehouse
ETL/ELT, transformation and data modeling
Data hygiene, quality, lineage and catalog
Least privilege, RBAC, ABAC and policy controls
AI Value
Decision intelligence, ML, GenAI and agents
Once the data is clean and governed, AI can support decision-making over enterprise policies, process documents, and business data through secured LLMs, RAG, MLflow, feature stores, and agentic workflows.
RAG over policies, processes and enterprise documents
LangChain-style orchestration and guardrails
Fraud and anomaly detection and prevention
Feature store, MLflow, ML and agentic AI
03 — Method
A connected path from assessment to delivery confidence.
Discovery & assessment, fit gap analysis and design, and phased delivery are tied together through workshops, documented scope, MVP milestones, backlog governance, and measurable decision points.
01
Discovery & assessment
2 – 6 weeks
Workshops establish business objectives, cloud and data scope, application and workload inventory, source-system discovery, report and KPI review, analytics discrepancy analysis, MDM ownership, network and integration baselines, risk posture, and migration readiness.
Cloud Assessment Report with 7R candidate view
Data discovery and analytics gap inventory
MDM owner and steward map
Infrastructure and network baseline
Risk & compliance findings
MVP scope and migration readiness scorecard
02
Fit gap analysis & Design
4 – 10 weeks
Current-to-target fit gap translates assessment findings into cloud migration strategy, 7R disposition, landing-zone design, network design, integration design, data platform blueprint, AI value blueprint, governance model, and phased roadmap.
7R migration and modernization analysis
Landing zone, network and security blueprint
Data platform and AI design blueprint
Phased roadmap with MVP milestones
Business case & TCO model
03
Delivery
8 – 16 weeks
Delivery runs in agile phases with agreed MVP scope, milestone demos, Scrum ceremonies, Jira backlog transparency, Confluence decisions, burn-up/burn-down visibility, and executive checkpoints before the final release.
Landing zone, network & migration waves
Integration, data platform & AI increments
Velocity, risk, dependency and burn tracking
Handover, runbooks & team training
04
Optimize
Ongoing
Continuous improvement turns delivery metrics into operating confidence across cost, reliability, security posture, service quality, AI/data quality, and roadmap iteration.
FinOps & performance tuning
Security posture management
Roadmap iteration, KPI reporting & adoption
04 — Advisory & delivery confidence
Confidence is built before the final delivery.
For a new startup, trust has to be earned early. Our approach gives leaders confidence through senior-led workshops, visible delivery controls, clear artifacts, and practical advice before a client commits to a large program.
Strategy and roadmap workshops
Short advisory workshops help clients validate cloud, data, AI, security, GTM, sales, delivery, or operating-model direction. This works when leaders need a second pair of experienced eyes before funding a larger program.
Startup-to-enterprise guidance
Startups can use our experience to think like an enterprise earlier: secure architecture, delivery governance, consultative selling, sell-to and sell-through motions, partner models, and hybrid delivery planning.
Enterprise-to-startup agility
Enterprises can move faster without ignoring risk: define an MVP, test assumptions, fail quickly in controlled increments, learn from feedback, and mature the solution through secure agile releases.
Transparent delivery controls
Scrum ceremonies, Jira backlog visibility, Confluence decisions, milestone demos, risk logs, dependency tracking, and burn-up/burn-down views show progress before the final handoff.
05 — Proof stories
Representative case studies that show how we think.
These anonymized examples are based on our migration, AI-ready data, and insurance fraud RAG solution materials. They are written for executives first, with enough technical detail to show delivery depth.
Cloud modernizationMigration factory
Large-scale migration and modernization with lower cutover risk
A legacy enterprise environment needed lower operating cost, faster provisioning, stronger governance, and a future-ready architecture. The approach used business-led discovery, dependency mapping, 7R classification, landing-zone governance, wave execution, CDC database migration, validation, rollback readiness, and hypercare.
Business issueHigh complexity, slow release cycles, aging infrastructure, fragmented DR, and rising compliance pressure.
Executive valueReduced migration uncertainty, clearer funding path, controlled downtime risk, and a modernization roadmap tied to business priorities.
Data platformAI-ready ecosystem
From fragmented analytics to governed data products
A business with scattered operational databases, SaaS data, streaming events, files, logs, and inconsistent reporting needed a trusted data foundation. The design used batch and streaming ingestion, cloud object storage, lakehouse and warehouse patterns, Bronze/Silver/Gold data products, governance, lineage, RBAC/ABAC, and BI/API enablement.
Business issueReports disagreed, KPI ownership was unclear, MDM gaps created rework, and AI use cases lacked governed data.
Our approachSource inventory, owner/steward mapping, medallion data design, dbt/Airflow orchestration, quality controls, access policy, and lineage.
Executive valueOne roadmap for trusted analytics, data sharing, APIs, ML features, and secure LLM context.
AI decision supportInsurance fraud RAG
Fraud investigation with governed RAG and human review
An insurance fraud solution needed to move beyond ad-hoc LLM prompts and basic ML scoring. The refined architecture used feature store signals, document intelligence, hybrid retrieval, LangGraph-style agent orchestration, MCP tool governance, validation agents, structured fraud verdicts, guardrails, audit events, observability, and human-in-the-loop escalation.
Business issueFraud decisions needed better evidence, traceability, confidence scoring, reviewer control, and audit readiness.
Our approachRetrieval-agentic workflow with claim facts, related claims, policy rules, evidence search, validation scoring, decision schema, and guardrails.
Start with a 30-minute fit discussion. If there is a match, we can produce a short advisory memo, reference architecture, or roadmap workshop proposal.
We focus where modernization is hardest — where downtime, compliance, and data sensitivity raise the bar on every decision.
BFSI
Banking, financial services, and insurance platforms with regulated workloads, real-time data, fraud intelligence, auditability, and zero-tolerance security postures.
Healthcare & Life Sciences
HIPAA-aligned cloud, clinical data, and AI for research & care delivery.
Public Sector
Secure modernization, FedRAMP-aware architectures, and citizen-data protection.
Retail & Manufacturing
Unified data, demand intelligence, and resilient global supply-chain platforms.
Global IT Providers
Subcontracted cloud, AI, data, and security delivery — extending your bench worldwide.
Hi-Tech & Telecom
Cloud-native platforms, network modernization, data integration, AI operations, service assurance, cybersecurity, and scalable customer experience ecosystems.
07 — Accelerators
Pre-built kits that compress weeks of work.
Opinionated starting points — battle-tested patterns, IaC modules, and playbooks that get you to outcomes faster without locking you in.
Discover
Cloud Readiness Kit
A packaged accelerator to assess, prioritize, and plan cloud adoption across infrastructure, applications, operations, and data platforms — from maturity baseline to 7R migration roadmap and executive business case.
Maturity assessment7R analysisTCO / ROIRoadmap
Build
GenAI LaunchPad
Secure reference architecture for enterprise GenAI — model gateway, prompt management, evaluation, and guardrails — on AWS Bedrock, Azure OpenAI, or GCP Vertex.
Model gatewayPrompt mgmtEval harness
Foundation
Lakehouse Blueprint
Opinionated Snowflake + Databricks medallion design with dbt models, Airflow orchestration, lineage, and data contracts — your single source of truth, ready for AI.
Bronze/Silver/Golddbt modelsLineage
Secure
Security & Compliance Validation
Automated control mapping for SOC 2, HIPAA, and PCI — with remediation playbooks tied to your cloud baseline.
Control mapGap reportRemediation plan
Deliver
Migration Factory & POD Model
Repeatable agile migration waves run by dedicated PODs — landing zones, IaC modules, runbooks, cutover playbooks, Jira tracking, and weekly KPI reporting.
Wave deliveryLanding zonesKPI cadence
Agentic AI
Agentic RAG Reference Stack
Production-grade LangChain / LangGraph orchestration with approved-source retrieval, validator, policy gates, audit trails, and human-escalation paths.
GuardrailsGroundednessTool permissions
Risk
Anomaly Detection & Risk Mitigation
Detect and prevent data-quality drift, suspicious access, policy violations, hallucinations, and unsafe tool actions — with continuous monitoring and exception workflows.
Drift detectionPolicy alertsHallucination defense
Operate
Managed Cloud & Data Ops
24/7 POD-based operations for cloud, data platforms, and AI workloads — predictable economics, defined SLAs, continuous optimization.
24/7 SREFinOpsQuarterly reviews
08 — About
A founder-led services firm built to earn trust before it earns work.
TalentPros Hub is a new professional services company led by practitioners with long enterprise careers in cloud, infrastructure, data, AI, integration, cybersecurity, compliance validation, and risk mitigation. Together, our founders have managed $100M+ in cloud, data, AI, and infrastructure transformation programs for Fortune 500 multinational companies and regulated organizations.
We bring senior architecture and security leadership into the first conversation, then recommend the smallest useful next step: assessment, fit gap design, roadmap, delivery POD, or risk review.
SR
Srinivasa (Srini) Rachapudi
Founder · Architecture, Pre-Sales & Cloud / Data / AI Delivery
Srini is a business-aligned technology transformation leader with 20+ years of experience guiding enterprises through cloud modernization, infrastructure programs, data platform builds, analytics modernization, and AI adoption. At TalentPros Hub he owns enterprise architecture, pre-sales strategy, and founder-led delivery — partnering with executive teams to turn modernization ambition into shipped, governed outcomes.
His prior enterprise leadership includes $52M+ in cloud order-booking experience during his Wipro tenure. That track record informs TalentPros Hub’s go-to-market discipline, executive solutioning, and delivery governance as a startup professional services firm.
His practice spans cloud modernization across AWS, Azure, and GCP; infrastructure and cloud network architecture; hybrid connectivity with AWS Transit Gateway and Azure ExpressRoute; data center modernization; data strategy and engineering roadmaps; MDM, owners and stewards; data platform architecture on object storage, Snowflake, Databricks, dbt and Airflow; and production AI with RAG, LangChain-style orchestration, feature stores, MLflow, vector pipelines, and guardrails — supported by DevSecOps and infrastructure-as-code practices.
Focus areas
Enterprise & cloud architecture
Infrastructure, data center & hybrid network design
Pre-sales strategy & solutioning
Cloud modernization · AWS / Azure / GCP
Integration & messaging architecture
Data strategy, MDM & analytics modernization
Data platform architecture & AI-ready ecosystems
AI / ML / GenAI / RAG delivery
DevSecOps & infrastructure as code
Credentials include PMP, AWS Solutions Architect, AWS DevOps Engineer Professional, Google Cloud Professional Cloud Architect, Microsoft Azure Administrator, ITIL 4, Scrum Master, and OneTrust Privacy (GDPR).
Prasad is a strategic program leader with 20+ years driving digital transformation, enterprise IT initiatives, and secure product delivery across healthcare, oil & gas, energy, defense, and retail. At TalentPros Hub he leads the cybersecurity and risk services practice — owning security architecture, compliance validation, and risk mitigation across every engagement.
His remit covers AI-powered GRC and continuous compliance, enterprise security architecture and KPIs for multi-cloud ecosystems, privacy and data governance with ServiceNow, OneTrust, and BigID, cybersecurity capability assessments, HITRUST/NIST alignment, OT/ICS security programs, healthcare cloud migration and data protection, and incident response programs.
Focus areas
Cybersecurity strategy & security architecture
Regulatory compliance & risk mitigation
GRC & continuous compliance platforms
Privacy & data governance · ServiceNow / OneTrust / BigID
HITRUST, NIST & OT/ICS security programs
Secure delivery & incident response
Industry experience across healthcare, oil & gas, energy, defense, and retail.
Enterprise modernization works when senior leaders own the outcome and security is engineered in, not bolted on. We bring both founders into every engagement and back them with disciplined global PODs.
Multi-decade enterprise technology leadership across both founders
Cloud + data + AI architecture paired with security leadership
$100M+ cloud, data, AI & infrastructure programs managed by the founders
$52M+ cloud order-booking leadership from Srini’s prior Wipro experience
AI-ready data ecosystem & Agentic RAG experience
Scalable POD-based global delivery
Founder-led, customer-first engagement
Why take the first discussion
New company, proven operators.
TalentPros Hub is a startup, but the work is led by practitioners with two decades of enterprise delivery experience. The first discussion is designed to earn confidence, not force a sales cycle. We review your objective, current environment, constraints, risks, delivery model, and possible next steps, then recommend whether an advisory workshop, short assessment, fit gap design, roadmap, delivery POD, or no engagement is the right answer.
Founder-led initial conversation, not a junior sales handoff
LinkedIn-verifiable careers across enterprise cloud, data, AI, infrastructure and cybersecurity
No inflated startup revenue claims: $52M+ is Srini’s prior Wipro order-booking experience
Clear next-step options: advisory workshop, assessment, fit gap design, roadmap, or delivery POD
Delivery confidence through MVP scope, Jira/Confluence governance, milestones, velocity and risk tracking
09 — Contact
Start with a focused discussion.
Tell us your business objective, current environment, risk concerns, and timeline. We will respond within one business day with a practical starting point: discovery and assessment, fit gap analysis and design, delivery, managed POD, or focused security review.
Start with a structured assessment or fit gap design. You get a clear view of current state, risks, options, cost drivers, and a roadmap your leadership team can review.