Digital engineering

Modernize. Accelerate.

Engineer for what's next.

Modernize. Accelerate.

Engineer for what's next.

Book a consultation

See how we work

The problem

Fix, replace, or rebuild?

Your legacy applications have become a bottleneck. Between fragile monolithic architectures, manual release cycles, and a codebase tangled in technical debt, your team is stuck in 'maintenance mode.' You aren't just managing old software, you're managing a growing barrier to your market growth.

You do not need another feature factory. You need an engineering partner who can modernize the foundation, accelerate delivery, and keep systems running reliably as you grow.

Solution overview

Lifecycle engineering: Build, run, & optimize

Lifecycle engineering: Build, run, & optimize

Tenjumps deploys cross-functional, AI-assisted engineering pods to modernize legacy platforms and build cloud-native futures. We don't ship code; we automate operations and embed quality to ensure your foundation scales without the friction of technical debt.

01

Enterprise application development

Cloud-native and intelligent systems

  • Modern architecture: We implement microservices, containerization, SRE, and DevSecOps to build scalable, resilient platforms.

  • Custom enterprise builds: We deliver bespoke workflow platforms, CRM and ERP extensions, and high-performance mobile and web apps.

  • AI-enabled features: Every application we build can integrate predictive analytics, recommendation engines, and automated audit intelligence.

  • Industry expertise: We provide deep domain engineering for logistics, BFSI, and manufacturing sectors.

02

Application sustenance and support

Reliability engineered for scale

  • L2/L3 production support: We provide 24x7 incident management, root cause analysis, and rigorous SLA/SLO-driven operations.

  • Technical debt management: We lean out operations through cloud cost optimization, license rationalization, and proactive code refactoring.

  • Modernization pathways: We handle seamless monolith-to-microservices migration, API enablement, and cloud re-platforming.

  • AI-driven operations: We deploy automated incident triage, self-healing scripts, and AI-based log analysis to reduce manual overhead.

03

Quality engineering

Continuous quality, not late-stage testing

  • Full-stack QA: Our automation-first practice covers functional, performance, security, and big data testing across the entire lifecycle.

  • Advanced framework tooling: We use behavior-driven development (BDD) with tools like Playwright, Selenium, and Rest Assured for rapid validation.

  • Shift-left methodology: We embed quality into the design phase to identify risks early and slash production defects.

  • Accelerated release cycles: We use risk-based testing and reusable components to improve speed-to-market and customer experience.

04

Intelligent automation

Self-optimizing enterprise systems

  • Lifecycle automation: We automate the end-to-end pipeline, including CI/CD, test execution, and infrastructure provisioning (IaC).

  • Process orchestration: We move beyond simple RPA to implement API-led automation and intelligent business workflow platforms.

  • AIOps and observability: We deploy self-healing systems with AI-powered event correlation and automated runbook execution.

  • Strategic governance: Every automation initiative is mapped to business KPIs and hardened by compliance and risk frameworks.

What our clients will see

Days to production systems

Days to production

8-30 days

Productivity gains

20-40%

Efficiency gains

60%+

Improvement in data accuracy

90%+

90%

Why companies choose Tenjumps

Tenjumps builds AI systems designed for production from the start. We connect AI to your data foundation, engineer the full model lifecycle, and deploy with built-in governance and compliance. By automating operations, we ensure your AI investment scales reliably. Every engagement is grounded in real business use cases, not technology demos.

Senior engineers from day one, not after the sale

The architects who assess your systems are the same engineers who build your solutions. No junior bench-padding, no handoff to a team you have never met. Our pods are led by engineers with 30+ years of individual experience who stay on your engagement from assessment through production and knowledge transfer.

AI-assisted delivery that multiplies engineering output

AI is not a feature we sell. It is how we work. Our delivery model uses agentic AI for requirements discovery, code generation, automated test case creation, and CI/CD pipeline management. This means faster builds, fewer defects, and production systems in 8-30 days without sacrificing quality or governance.

Built to hand off, not to lock in

Every engagement includes knowledge transfer, standardized engineering practices, and team enablement. We build governance and transparency into the operating model so your internal teams can own and extend the systems we deliver. If you need ongoing support, our operations pods are available. But the choice is yours.

Success stories

Results that speak for themselves

60%

of tickets resolved instantly

Customer service automation

The Challenge: A logistics leader was overwhelmed by 150+ daily emails—83% of which were repetitive shipping queries.

The Solution: Tenjumps deployed an AI chatbot trained on historic email patterns in just 60 days.

The Result: 60% of tickets resolved automatically without human intervention.

  • 24/7 global support across 200+ countries.

  • CS reps redirected to high-value, complex cases.

99%

reduction in candidate verification time

HR automation

The Challenge: A financial services firm had a 4-month hiring lag due to manual recruiter verification.

The Solution: We built an agentic AI solution in only 10 days to automate re-engagement and LinkedIn verification.

The Result: 70% candidate re-engagement with 90% matching accuracy.

  • Delivery time slashed from 4 months to 4 weeks.

  • Eliminated weeks of manual searching for the team.

Featured

Read our latest insights on digital engineering

How we evaluate, deploy, and govern AI with your team.

Read more

Read more

How we work

AI-assisted delivery through cross-functional pods

Every digital engineering engagement runs through our Business Excellence Model (BEM) and is executed by a cross-functional pod: a self-contained, autonomous unit that collaborates with AI to deliver end-to-end application development. Our AI-assisted delivery model uses agentic AI for code generation, requirements discovery, automated test cases, and CI/CD automation, while human engineers own architecture, design decisions, and quality governance.

01

Explore

Strategy & Readiness

We audit your data foundation and infrastructure to identify high-value use cases. The output is a prioritized roadmap based on technical feasibility and business ROI.

02

Engage

Architecture & Governance

We select the right tech stack—RAG, agents, or ML—and design for scale. For regulated industries, we bake in compliance frameworks and guardrails before a single line of code is written.

03

Execute

Agile Deployment

Our engineering pods build and ship. Whether it’s GenAI agents, MLOps pipelines, or intelligent automation, we deploy with full observability, auditability, and governance from day one.

04

Evolve

Optimization & Autonomy

We monitor for drift, bias, and performance, building feedback loops for continuous retraining. Our goal is to mature your internal AI capability so you own the platform.

Related content

Insights from our team

Explore all insights

Explore all insights

Data Quality

Cost of poor data quality

A single data quality issue cost 50 engineering hours last quarter. Only 6 were tracked. Paleti Lakshmikanth breaks down where the hidden time goes.

Data pipeline

Production data engineering: what tutorials never teach you

Production data engineering looks nothing like tutorials. Kavya Kumari shares what actually changes when pipelines run at scale and stakeholders are waiting.

Responsible data engineering

Cloud cost optimization: The 50GB report nobody reads

For the 50GB weekly export, 47 recipients receive it, but only 3 open it. Bhavya Venu breaks down how wasteful data exports drain cloud budgets and what to do about it.

FAQs about digital engineering

What types of applications do you build?

We build cloud-native applications, bespoke enterprise platforms, and AI-enabled intelligent applications. This includes CRM and ERP extensions, enterprise workflow platforms, web and mobile apps, chatbots, reporting systems, and custom business tools. We also build AI-enabled features such as recommendation engines, predictive analytics, conversational interfaces, and automated audit intelligence. Our primary verticals are logistics, BFSI, and manufacturing.

Can you take over support and maintenance for applications we have already built?

Yes. Our application sustenance practice provides L2/L3 support, incident and change management, SLA-based managed services, and 24x7 production monitoring. We also manage technical debt by auditing your codebase, optimizing cloud costs, rationalizing licenses, and recommending refactoring priorities. For legacy systems, we handle monolith-to-microservices migration, API enablement, and cloud re-platforming.

What is an AI-assisted delivery model?

Our delivery model embeds AI directly into the engineering process. Agentic AI assists with requirements discovery from documents and tickets, code generation, automated test case creation, traceability, and CI/CD release management. Human engineers own all architecture and design decisions, quality governance, and client communication. The result is faster delivery, fewer human errors, and production-quality output from smaller, more senior teams.

How do you approach quality engineering?

We embed quality into the full development lifecycle, not just the testing phase. Our approach follows three stages: engage (test strategy, infrastructure, tooling), execute (functional, integration, regression, performance, and acceptance testing), and evolve (reusable components, risk-based testing, continuous automation). We use coded UI automation and behavior-driven frameworks with industry-standard tools. The outcomes are faster release cycles, reduced production defects, and improved customer experience

What industries do you work in?

Our digital engineering practice focuses on logistics, financial services (BFSI), and manufacturing. We bring deep domain knowledge in each vertical, which means our engineers understand your business context, compliance requirements, and operational constraints, not just the technology stack.

How does Tenjumps pricing compare to larger firms?

Our teams are senior-only, which means a higher day rate than offshore-heavy firms but significantly fewer total days to production. Our AI-assisted delivery model further compresses timelines by automating routine engineering tasks. When you factor in total cost of engagement rather than rate card alone, our model consistently delivers better ROI, with mid-market clients averaging an 8-month payback period.

What does a typical engagement team look like?

What does a typical engagement team look like? We deploy self-contained pods, each led by a team lead and scrum master, with developers, QA engineers, DevOps support, and agentic AI integrated into the workflow. Pods are cross-functional, autonomous, and own end-to-end responsibility for delivery. A typical pod includes 6-10 people depending on scope, with a client lead and product owner embedded in the structure for alignment.

Ready to modernize your applications and accelerate delivery?

Whether you need to build something new, modernize what you have, or get better at running what is already in production, we can show you what is possible in your first conversation.

Book a consultation