Enterprise software ships late: slow release cycles, monoliths that resist change, and a thin internal team. Flentas builds, bridges and modernizes cloud-native applications on AWS, delivered through an AI-driven lifecycle with a human gate at every step. Build new · Bridge legacy · Modernize · Operate.
Most delivery problems aren't about effort. They're structural. Slow pipelines, legacy that resists change, and a skills gap compound until every release slips.
Slow release cycles and a roadmap bottlenecked on a thin internal team.
A monolith that's hard to scale and costly to maintain blocks every new feature.
Systems that don't talk, manual handoffs and inconsistent data flow slow everything down.
Senior cloud, DevOps and modern-framework skills are scarce and slow to hire.
Stagnant infrastructure, no automation and heavy support overhead drain the budget.
Downtime, performance bottlenecks and no automated testing erode trust.
All three run on the same delivery playbook, the same accelerators and the same engagement models.
Cloud-first from day one: microservices, serverless, DevOps by design. For new products and platforms that must scale.
Secure on-premise systems meet modern apps: hybrid gateways, SPA/PWA web, enterprise mobile. For enterprises with protected data that isn't moving.
Migrate, modernize or build MVPs: strangler-pattern refactoring, API engineering, multi-tenant SaaS. For monoliths, ISVs and SaaS launches.
In 2026 the bottleneck isn't writing code. It's knowing what to build, proving it works, and understanding what a change will break. So we run an AI-driven lifecycle on top of the playbook, not instead of one.
Requirements, stories, code, tests and runbooks.
Every AI-generated artifact passes a gate.
Every PR risk-scored before merge.
A CCOE-approved practice on every project.
An Agile SDLC (Scrum and Kanban) mapped to six delivery phases: transparency, continuous delivery, rapid value realization.
Gate: BRD/FSD, architecture and plan approved by you.
Gate: POC demo, go/no-go.
Gate: sprint demo accepted.
Gate: QA report green, security scans clean.
Gate: cutover plan executed, hypercare exit.
Gate: SLA met, CSAT reviewed.
We align to AWS's AI-Driven Development Life Cycle (AI-DLC): AI plans, asks and drafts; the team validates before anything is built. Every unit of work moves the same way, AI proposes, team verifies, AI generates and tests, in hours-to-days cycles inside your sprint.
AI drafts requirements, user stories and units of work; the team validates in one session. Gate: you approve what gets built, and why.
AI proposes architecture and generates code, tests and docs; humans steer at every checkpoint. Gate: human review before every merge.
AI drafts IaC, runbooks and release notes; AI-assisted incident triage against project context. Gate: named humans approve changes and hold production access.
ChangeSafe AI, our IP, turns your repositories into a live, confidence-scored architecture graph: up to 7× fewer tokens per AI architecture query, 10× faster onboarding onto any codebase, and every PR's blast radius scored before a human opens it. Runs 100% in your AWS account. Code never leaves your VPC.
Independent, scalable services on Docker and Kubernetes (Amazon EKS).
Event-driven architectures on Lambda and API Gateway, near-zero operational overhead.
CI/CD, Infrastructure-as-Code and VAPT scans from day one.
Secure protocols between protected on-prem databases and cloud front ends.
High-performance SPAs and PWAs in React and Angular.
Cross-platform and native iOS/Android applications.
Strangler-pattern migration to cloud with near-zero downtime.
Documented RESTful and GraphQL layers connecting disparate systems.
Secure data isolation and scalable tenant provisioning.
An 80% unit-test coverage floor reported in the pipeline, a six-state Jira workflow, and a release-per-sprint Git strategy.
Every sprint gets a full QA sprint (N+1) on its own release branch; nothing reaches main until QA passes.
Every commit and every build is scanned; builds fail on findings; zero unscanned builds.
Structured logs, shared dashboards, and three alert severities each linked to a runbook; releases run from a documented runbook with zero-downtime cutover.
Production-tested, proprietary assets we bring to every engagement, so Sprint 1 starts from a working baseline, not a blank repository.
Scanning, gates and deployment stages ready on day one.
Spring Boot, Angular and Node.js starters with our standards built in.
Accessible, themeable components for web and mobile.
Patterns and adapters for connecting enterprise systems.
Approved landing zones and Terraform modules.
A live dependency graph on every repository.
Kiro and Claude Code on Amazon Bedrock, governed by the playbook.
Insurance / IRDA
Zero
Mahindra Insurance Brokers: one platform for motor and non-motor insurance. Decoupled, API-driven microservices (Angular + Spring Boot), containerized on Amazon EKS, Jenkins CI/CD, SonarQube, WAF, GuardDuty and full observability. IRDA-aligned compliance with DR, audit logging and PII masking.
Godrej Capital
“Flentas has been an integral technology partner from design inception to building and managing our Enterprise Applications and infrastructure on AWS Cloud.”
Jyothirlatha B.CTOGodrej Capital
Every model runs on the same delivery discipline. The gates don't change with the commercial model.
Locked requirements and a hard date: a predictable budget mapped to phases and milestones.
Long-term Agile pods that scale up or down; you keep direct control of the backlog.
Evolving products that pivot quickly; pay strictly for engineering hours consumed.
24/7 SLA-driven incident management, L2/L3 support, monitoring and security patching.
A senior pod running the AI-DLC model in your AWS account; priced on outcomes or capacity.
Advanced Consulting Partner with GenAI Competency; cloud-native engineering is our core practice.
FinTech, InsurTech, Gaming and high-scale consumer applications across India and the GCC.
CCOE-governed delivery: fixed cadence, engineering standards, shift-left security and 14 handover artefacts on every project.
AI in every phase, a human at every gate, ChangeSafe on every repository.
Proprietary pipelines, boilerplates and component libraries that take weeks off the plan.
99.99%+ uptime at Godrej Capital · zero-downtime releases at Mahindra Insurance Brokers · a 40% shorter procurement cycle at Jaleel Holdings.
Requirement workshops, technical audit, target architecture, MVP milestones and estimation plan. You approve the plan.
Prove the riskiest piece first; a ChangeSafe run on your repositories gives you the full dependency map on day one.
The playbook cadence from Sprint 1: two standups a day, three fixed calls a week, QA lane N+1.
One engagement is one stage. Here is what usually comes before and after, so the next step is always clear.
Clear the application and database debt that migration alone does not solve.
Explore Application and Database ModernizationMicroservices, containers and CI/CD so you ship every day.
Make every release a routine, low-risk event.
Explore DevOps and AutomationOne governed copy of your data, ready for BI and AI.
Explore Data EngineeringBook the discovery workshop and leave with an approved plan: target architecture, MVP milestones and an estimate you can take to the board.
