Data & API Engineering
We build the data backbone your product runs on — ETL/ELT pipelines, secure REST and GraphQL APIs, event streaming and analytics-ready warehouses — engineered for correctness, low latency and scale. Not brittle scripts. Governed, observable data infrastructure that holds up in production.
Trusted engineering behind ProtectComply (India’s DPDP compliance platform) and IntelloWork (enterprise search & RAG chatbot).
Data Engineering for Scalable Data Pipelines
The difference between a dashboard you trust and one you second-guess is the pipeline underneath it. We design ingestion and transformation that stays correct as volume, sources and schemas change.
Reliable Data Pipelines for Modern Systems
We build ETL and ELT pipelines with schema validation, idempotent loads and data-quality checks at every stage — so bad records get caught early instead of surfacing as wrong numbers in a board deck.
Whether your data lands in Snowflake, BigQuery, Postgres or a lakehouse, we architect for both batch and streaming, with lineage and retries built in so a failed run recovers cleanly instead of silently dropping rows.
API Engineering for Seamless System Integration
APIs are the contract between your systems and everyone who depends on them. We design them to be predictable, versioned and hard to misuse — the same discipline that lets ProtectComply and IntelloWork ship features without breaking their clients.
Connect Applications, Platforms and Cloud Services
We build REST and GraphQL APIs with authentication, rate limiting, pagination and clear error semantics — documented with OpenAPI so your team and your partners integrate in hours, not weeks.
For integration-heavy stacks we design event-driven and webhook architectures that keep CRMs, ERPs, payment providers and third-party tools in sync without fragile point-to-point glue that breaks on every change.
Real-Time Data Processing and Analytics Enablement
When a decision can’t wait for tomorrow’s batch, you need streaming. We build event pipelines that turn raw activity into signals your product and your team can act on in seconds.
Streaming Data for Instant Intelligence
Using Kafka, Kinesis or managed pub/sub, we build streaming architectures that process events as they happen — powering live dashboards, usage metering, fraud and anomaly detection, and in-product personalization.
The same real-time foundation feeds analytics-ready tables, so operational events and business intelligence share one trustworthy source instead of drifting apart in separate systems.
Secure, Governed and High-Performance Data Ecosystems
Data you can’t govern is a liability. We engineer platforms where access, retention and privacy are enforced in code — the exact standard we hold ourselves to building ProtectComply’s DPDP compliance platform.
Security, Compliance and Low-Latency Performance
Role-based access control, encryption in transit and at rest, PII handling and full audit logging are built into the pipeline — not bolted on later — so you can prove who touched what data and when.
We tune queries, indexes, caching and connection pooling so your data and APIs stay fast and available under real production load, with monitoring and alerting that catches degradation before your users do.
Data & API Engineering Capabilities
Everything you need to move from scattered spreadsheets and one-off scripts to a connected, governed and analytics-ready data platform.
Data Pipeline Engineering
ETL/ELT pipelines for batch and streaming data, with validation, lineage and clean recovery from failed runs.
API Development
Secure, versioned REST and GraphQL APIs documented with OpenAPI, built to be easy to integrate and hard to misuse.
System Integration
Event-driven and webhook integrations that keep CRMs, ERPs, payment and third-party tools reliably in sync.
Real-Time Processing
Kafka, Kinesis and pub/sub streaming for live dashboards, metering, and anomaly detection in seconds.
Data Quality
Automated checks, tests and monitoring so teams trust the numbers instead of reconciling them by hand.
Data Governance
Role-based access, PII handling, retention and audit logging — DPDP-aware and compliance-ready by design.
Analytics Enablement
Modelled, warehouse-ready tables that feed BI, reporting and decision systems from one source of truth.
High-Performance APIs
Caching, query tuning and load-tested endpoints optimized for low latency and high availability at scale.
Enterprise Data & API Architecture
Modern enterprise ecosystems require reliable data ingestion, secure APIs, governed access and analytics-ready pipelines.
Ingest
Collect data from applications, databases, APIs, events and enterprise platforms.
Process
Clean, transform, validate and structure data for business and technical use cases.
Integrate
Connect systems through secure APIs, services and real-time integration layers.
Analyze
Enable dashboards, reporting, predictive insights and real-time operational intelligence.
How We Build
A pragmatic path from scattered data to a platform your team relies on every day.
Map & Audit
We inventory your sources, schemas and consumers, find the data-quality gaps, and define what “correct” means before writing a line of pipeline.
Design the Contracts
We model the warehouse and design API contracts up front — schemas, SLAs, access rules — so downstream teams build against a stable foundation.
Build & Instrument
We ship pipelines and APIs with validation, tests, lineage and monitoring wired in, so failures are visible and recoverable, not silent.
Harden & Scale
We load-test, tune performance, lock down governance and hand over runbooks — then scale to new sources and consumers with confidence.
Data & API Engineering FAQs
What’s the difference between ETL and ELT, and which do we need?
ETL transforms data before loading it; ELT loads raw data into a modern warehouse (Snowflake, BigQuery) and transforms it there. ELT is usually the better fit for cloud warehouses and large volumes, while ETL still makes sense when you must clean or mask data before it ever lands. We pick based on your sources, compliance needs and cost, rather than defaulting to one.
Can you work with our existing data warehouse and cloud?
Yes. We’re warehouse- and cloud-agnostic — Snowflake, BigQuery, Redshift, Postgres and lakehouse setups on AWS, Azure or GCP. We build on top of what you have rather than forcing a rebuild, and only recommend migration when the current setup is genuinely holding you back.
How do you keep our data secure and DPDP-compliant?
Governance is built into the pipeline: role-based access control, encryption in transit and at rest, PII masking, retention rules and full audit logging. It’s the same DPDP-aware discipline we applied building ProtectComply, so you can demonstrate exactly who accessed which data and when.
Our APIs keep breaking integrations when we change them. Can you fix that?
Yes — that’s a versioning and contract problem. We introduce proper API versioning, OpenAPI-documented contracts, backward-compatible changes and deprecation policies so you can evolve your APIs without breaking the teams and partners who depend on them.
Do we need real-time streaming, or is batch enough?
It depends on the decision the data drives. If a delay of hours is fine — most reporting — batch is cheaper and simpler. If you need live dashboards, usage metering, or fraud and anomaly detection, streaming earns its keep. We often run both from one architecture and help you decide per use case instead of over-engineering everything.
Build Data & API Systems That Power Scalable Growth
Tell us where your data or integrations are slowing you down. We’ll tell you honestly what to fix first — and how we’d build a secure, high-performance foundation for automation, analytics and enterprise integration.
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