Data & Analytics Automation is the process of using workflows, APIs, and orchestration tools to streamline how data is collected, processed, and utilized. Instead of manually syncing reports or running batch scripts, automated pipelines ensure that data flows from sources to destinations in real time or on a schedule. This improves decision-making, reduces human error, and frees teams to focus on analysis rather than maintenance.
Our approach ensures high data integrity, modular architecture, and real-time adaptability.
We identify and catalog all relevant data sources—internal and external, structured or unstructured—to map your data landscape.
We create scalable, resilient pipelines for ingestion, transformation, and storage across modern data warehouses and lakes.
We implement automated ETL/ELT jobs and real-time syncs using orchestration tools to eliminate manual workflows.
We integrate data with BI tools and custom apps to turn raw data into operational insights and AI-ready assets.
Data warehouses, BI tools, stream processors, and AI frameworks.
An open-source workflow automation tool. We use it for complex integrations and advanced logic.
Makers of GPT models. We use OpenAI’s APIs for tasks like summarization, classification, and more.
An emerging open-source LLM platform focused on developer-friendly automation.
Creators of Claude, a highly capable AI assistant with strong reasoning and safety alignment.
Google’s flagship AI model suite. We use it for enterprise-grade AI features and experiments.
Meta’s LLaMA models power on-device and private AI use cases. We use it for RAG and inference tasks.
A vector and analytics platform for AI workflows. Great for RAG, search, and classification.
A powerful no-code automation tool. We build scalable, visual workflows across many tools.
A simple way to connect web apps and automate repetitive tasks with minimal configuration.
We use Python for custom logic, scraping, automation scripts, and advanced backend workflows.
An LLM orchestration library. We use it to build custom AI agents and contextual pipelines.
Amazon Web Services for cloud computing, storage, and serverless functions. We deploy our solutions here.
...and over 7000+ applications we seamlessly integrate with.
If an application does not have a direct integration with our systems, we use their APIs to connect seamlessly.
Every data workflow we build is modular, reliable, and ready for scale.
Streamline data ingestion, transformation, and loading with minimal manual intervention.
Support for both traditional ETL and modern ELT architectures using dbt, Airbyte, or custom scripts.
Enable live metrics dashboards and event-driven systems using Kafka, Pub/Sub, or stream processing engines.
Catch anomalies early with automated checks, schema validations, and exception logging.
Prepare and serve data pipelines directly into machine learning models and AI agents.
Leverage the elasticity of cloud storage and compute to handle high-volume, high-velocity data workflows.
Let’s build smarter data workflows—from ETL to ML—with less overhead and more insight.
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