LangGrant, formerly Windocks, is relied on by enterprises around the world since 2015, and known for technical innovation and responsive support.
We’re dedicated to surpassing client expectations, and living by the principle of doing more with less. We enjoy automating data processes with DevOps and DataOps principles, and more recently with Large Language Models (LLMs), and working with like-minded customers.
We’ve also received recognition from the industry at-large. Gartner has recognized us consistently, early in our history with a “Cool Vendor” and more recently for our innovation in Synthetic data.
What we prioritize
Data automation is a journey
We aim to serve you at any phase of your automation journey, beginning with self-service data and progressing to scheduled and automated delivery on-demand through CI/CD, alongside technologies such as Kubernetes.
Work with existing infrastructure
We are often frustrated when adopting new practices requires swapping out underlying technologies. We design our systems to work with your existing Oracle, SQL Server databases and storage, either on-premise or public cloud.
Keep the platform open
While we strive to deliver a complete solution, Windocks allows you freedom to plug in any data masking, synthetic data generation, authentication, or storage.
Accessible
Our software is downloadable, up-and-running in minutes, and easily evaluated. We also make ourselves available to meet online when needed, and prioritize new features and functions according to your needs.
Gartner analysis
Windocks included as key vendor in Gartner report
Windocks was included in Gartner’s recent report “Emerging Tech Impact Radar: Data and Analytics.” The renowned consulting firm named Windocks as a key vendor in the tabular and synthetic data.
UP CLOSE
Bloor analyst report on test data management
Bloor described Windocks as “an up-and-coming database virtualisation vendor that it looks like might be poised to shake up the space.”
Press
News highlights
Recent breakthroughs in advanced reasoning LLMs now offer the potential to fundamentally reshape the relationship between AI, data engineering, and analytics.
LangGrant applies LLMs and AI assistants to operational data in orgs that face restrictions on data movement and concerns over cost.
Ramesh Parameswaran shares his career journey from Microsoft to startups, focusing on the evolution in database modernization and AI. He stresses the need to understand database semantics for AI effectiveness.
The server eliminates the need to rely on application developers and data engineers to manually join data sets before AI agents can invoke a data set.
The server automates delivery of database context, without revealing any enterprise data, and enables the LLM to design analytic pipelines while complying with enterprise security and governance.
LangGrant orchestrates LLMs to deliver results while still complying with enterprise data policies. Analytics and reasoning occur using metadata and schema context – no raw data or large payloads are transmitted to the LLM.
“…there’s no doubt there will be a corresponding rise of interest in database virtualization technologies that promise to make it simpler to build those types of applications.”
“A new DevOps database platform can allow the databases to be treated like any other DevOps artifacts that are orchestrated and automated within the DevOps toolchains.”
“. . . provided users with the features they were waiting for from Microsoft, such as the ability to support .NET and SQL Servers in containers while running Windows Server.”
“And one of the key differences between the Windocks containers and Microsoft’s official container support for Windows turns out to be quite surprising: compatibility with existing applications and processes.”
“LEDGE MCP Server does not expose data to LLMs, removes token costs as a barrier to Agentic AI, and delivers accurate, executable multi-step analytics plans.”
“LangGrant (formerly Windocks) has launched the LEDGE MCP Server, an orchestration and governance engine for large language model (LLM) enterprise database access. “
“LangGrant has announced its LEDGE MCP server that enables LLMs to reason across multiple enterprise databases and generate multi-step analytics plans without transmitting raw data to the model. The system works entirely with metadata and schema context.”
Social Media
Featured Customers
LIFE SCIENCES
Novartis
World’s second largest pharmaceutical company by market cap. Shares R&D data across multiple research centers worldwide.
RETAIL
DriveTime
Innovative company utilizing proprietary tools and processes to redefine the process of purchasing, financing, and protecting vehicles.
INSURANCE
American Family Insurance
Third-largest mutual property/casualty insurance company in the U.S. Automates the delivery of applications in its direct-to-consumer business.
FINANCIAL SERVICES
DoubleLine
Money management firm employing active risk management, in-depth research, and innovative product solutions. Employs analytical systems developed and maintained in-house.
Leadership
Ramesh Parameswaran
CEO, CTO, and Cofounder
Veteran of Microsoft leading its UNIX initiatives and serial entrepreneur. Founder of a Top 100 website in Web 1.0.
Paul Stanton
VP of Product Management and Cofounder
Veteran of Microsoft and recognized expert in PaaS, open source, Test Data Management, and DevOps.
Steve Pao
VP, Data Science
Veteran of Oracle and serial startup executive across data-intensive fields of cybersecurity and data protection. 2 IPOs.