Alliances & Collaborations

A fully managed, cloud-native data integration service, Google Cloud Data Fusion enables the design and deployment of ETL/ELT pipelines through a visual interface. It simplifies complex data workflows, accelerates time to insight, and ensures seamless integration across on-prem, multi-cloud, and SaaS data sources with built-in scalability and governance.

We leverage Groq’s cutting-edge LPU™ (Language Processing Unit) technology to deliver ultra-low-latency inference for large language models and generative AI workloads. With GroqCloud™ and GroqRack™, we accelerate real-time applications—enabling deterministic performance, high throughput, and cost efficiency across enterprise AI deployments in NLP, vision, and decision intelligence.

We leverage Hugging Face's open-source ecosystem to accelerate AI development across NLP, vision, and multimodal applications. With access to over 900,000 models, 200,000 datasets, and 300,000 demo apps via the Hugging Face Hub, we streamline model deployment, fine-tuning, and evaluation. Key tools like the Transformers library, Datasets, Evaluate, and Gradio enable us to build and deploy state-of-the-art AI solutions efficiently.

Built for orchestrating complex, stateful AI workflows, LangGraph enables the creation of multi-agent systems with dynamic control flows and persistent memory. We use LangGraph to design advanced applications that require coordination, long-term context, and decision-making—ideal for reasoning agents, process automation, and adaptive conversational systems.

We use Looker Studio to deliver flexible, easy-to-share dashboards that connect directly to live data sources like BigQuery, Sheets, and GA4. Its integration within the Google ecosystem allows us to build cost-effective, collaborative BI solutions for marketing, finance, and operations teams.

Microsoft Azure offers a comprehensive suite of cloud services for developing, deploying, and managing applications at scale. Leveraging components like Azure Data Factory, Synapse Analytics, and Microsoft Fabric, we architect hybrid, enterprise-grade data platforms with robust security, advanced analytics capabilities, and seamless interoperability across multi-cloud and on-premises environments.

Purpose-built for unified analytics, Microsoft Fabric seamlessly integrates data lakes, pipelines, and reporting into a single platform. We leverage its lakehouse architecture, real-time streaming, and native Power BI integration to streamline data engineering, accelerate model development, and deliver insights at scale across cloud and enterprise environments.

With a team of 75+ Power BI professionals, we specialize in delivering interactive, enterprise-grade dashboards and analytics solutions. Power BI enables us to transform complex data into intuitive visualizations, drive real-time insights, and empower business users across functions with self-service analytics and seamless integration into Microsoft’s data ecosystem.

We leverage OpenAI’s latest models—including GPT-4o, GPT-4.1, DALL·E 3, Whisper, and Codex—to power advanced AI solutions across language, vision, audio, and code. These models enable intelligent automation, multimodal experiences, and real-time decision support, driving innovation in enterprise workflows, customer engagement, content creation, and software development.

Widely adopted for AI research and production, PyTorch offers dynamic computation graphs and native Python integration, making it highly intuitive and flexible. We leverage PyTorch to develop deep learning models for computer vision, NLP, and reinforcement learning—enabling rapid prototyping, seamless deployment, and scalable training across GPUs and distributed systems.

We leverage Python as a foundational language for data engineering, analytics, and machine learning. Its extensive libraries—such as Pandas, NumPy, Scikit-learn, and PyTorch—enable rapid development of data pipelines, statistical models, and AI solutions. Python's versatility ensures seamless integration across cloud platforms, APIs, and enterprise data environments.

As official partners, we architect and implement Snowflake’s cloud-native data platform to power scalable, high-performance analytics. We leverage its multi-cluster shared data architecture, native support for semi-structured data, and advanced features like Snowpipe, Data Sharing, and Snowpark to build robust, secure, and future-ready enterprise data ecosystems.

We work extensively with Tableau to build interactive dashboards and rich visual analytics that drive data-driven decision-making. Its drag-and-drop interface, powerful data blending, and storytelling capabilities allow us to deliver scalable BI solutions that empower users to explore insights independently across all business functions.

An industry-standard deep learning framework, TensorFlow enables us to build, train, and deploy robust ML models at scale. We leverage its flexible architecture and ecosystem—including TensorFlow Extended (TFX) and TensorFlow Lite—for developing end-to-end AI solutions across cloud, mobile, and edge environments in vision, NLP, and forecasting use cases.