Selected engineering work

Intelligent applications. The systems that make them work.

Explore how we connect AI, product workflows, data, and backend systems. The first three stories follow a private platform we are building; the others draw on Ajay's earlier engineering roles.

Enterprise AI

An AI product needs more than a model.

See how we are connecting a useful AI workflow to the business context and controls it needs.

Confidential platform · in development

An AI workspace grounded in business context.

We are bringing business data and AI assistance into the same product workflow, with access and review designed into the experience.

AI applicationProduct workflowAccess control

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The need

Help people act on information spread across product and external systems.

Our work

Connect user context, AI processing, permissions, and review in one workflow.

Current stage

The platform and its AI workflows are being developed.

Backend platforms

What connects the application to the real world.

The data and service work that lets a product operate across existing systems.

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Illustrative artwork

Backend platforms & integrations · In development

Getting source data into a form the product can trust.

We are building the ingestion and recovery paths that turn external data into dependable product input.

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Access & operations · In development

Keeping the platform dependable across service boundaries.

We are defining how identity, product services, and background work stay consistent as the platform grows.

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Earlier experience

Engineering depth from work before Cimulink.

At Arcesium, Slice, SAP Labs, and Prudential, Ajay worked on performance, banking, GDPR-related data retention, and payment systems.

Ajay at ArcesiumStreaming more data with less memory.At Arcesium, Ajay improved OData streaming performance through pagination and serializer work.Ajay at SliceA distributed limit on a core banking path.At Slice, Ajay engineered a distributed rate limiter for a core banking system.Ajay at SAP LabsEngineering data retention for GDPR requirements.At SAP Labs, Ajay built a service for sensitive employee records and a GDPR-related retention tool with controlled deletion paths.Ajay at PrudentialA recurring payment path for insurance policies.At Prudential, Ajay designed and implemented recurring payments based on established policy mandates.

How we approach the build

Start with the work people need to do.

01 / Workflow

Find the actual task

Identify the user, decision, and point where software can help.

02 / Systems

Map the boundaries

Check data, permissions, existing services, and failure paths.

03 / Delivery

Build in working slices

Validate behavior, operation, and ownership as scope grows.

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What are you building?

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