Safe, governed use of LLMs begins with an automated database context that enables LLMs to comprehend databases, without exposing data.
Your governance policies
The server runs within the firewall, and enterprise data stays within enterprise governed systems.
LangGrant runs within your established security policies, including masking for sensitive data, on enterprise databases including Oracle, Oracle EBS, SQL Server, Snowflake, Aurora, PostgreSQL, MySQL, as well as cloud hosted data services on OCI, AWS, and Azure.
Data sovereignty
Safe use of LLMs includes freedom to use public LLMs without exposing data, as well as private models. LangGrant runs wherever needed, including private infrastructure, a laptop, or public cloud. This flexibility ensures that data sovereignty needs are easily addressed.
Token budgeting
A growing and practical concern in use of LLMs is token usage and costs. LEDGE server includes robust token budgeting, for charge back, and general LLM usage.
Explore more capabilities
Automated database context
LangGrant automatically delivers complete database context for LLMs to comprehend multiple databases simultaneously at scale. Like a skilled engineer, once an LLM understands databases it can contribute to solution design.
Micro data lakes on demand
LangGrant binds LLMs to create accurate analytic plans for user queries, resulting in a inference ready “micro data lake.” Plans are saved, easily validated and modified, and run to deliver the analytic data within minutes of the user query.
Governance
PII safeguards, authorization controls, data residency rules, firewall restrictions, and token-governance policies are built-in by design. No sensitive data leaves governed systems.
Plan management
LLM generated plans are saved, easily reviewed and validated, modified, and executed, for LLM use that is transparent, explainable, and repeatable.
Database cloning and containers
On demand database clones with containers provide Agent developers with production database copies (with optional masking) for agentic AI dev/test.
Database subsetting and synthetic data
Database subsetting with synthetic data provides added context for working with complex multi-database environments.