Yes - RESTful API for programmatic query execution
About LMQL
LMQL (Language Model Query Language) is a specialized query language that enables enterprises to interact with large language models through natural language syntax. Rather than building complex prompt engineering pipelines, users write declarative queries that leverage LLMs for data analysis, information extraction, and intelligent data processing at scale. The platform simplifies the integration of AI capabilities into existing data workflows, allowing technical and non-technical users to extract actionable insights from unstructured data without deep machine learning expertise. AiDOOS enhances LMQL deployment by providing enterprise-grade governance, managed infrastructure, seamless integration with data pipelines, and optimization of LLM usage costs. Organizations benefit from rapid time-to-value, reduced development overhead, and the ability to scale AI-powered data analysis across departments without managing underlying model infrastructure.
Challenges It Solves
Complex prompt engineering required to extract insights from LLMs
Difficulty integrating AI capabilities into existing enterprise data workflows
High costs and latency when running LLM queries at scale
Lack of governance and auditability in AI-driven data analysis
64
Faster time-to-insight using natural language queries
48
Reduced development costs for LLM integration projects
35
Improved query accuracy with declarative syntax
Use Cases
Document Intelligence & Extraction
Automatically extract structured information from unstructured documents, contracts, and reports using natural language queries without manual annotation.
72%70% reduction in document processing time
Customer Sentiment Analysis
Analyze customer feedback, reviews, and support tickets at scale to identify trends, sentiment, and actionable insights in real-time.
58%Accurate sentiment classification across thousands of records
Research & Knowledge Discovery
Query large knowledge bases and research databases to discover patterns, connections, and insights across unstructured content.
65%Accelerated research timelines with intelligent querying
Data Validation & Quality Assurance
Apply complex validation rules and quality checks to datasets using natural language logic without writing code.
52%Improved data quality with automated rule enforcement
Pricing
Pricing available on request
LMQL pricing is customized based on your team size, integrations, and requirements. AiDOOS will get you a scoped proposal — for free.
AiDOOS-verified review data is collected after deployment. Deploy this product and be among the first to share your experience.
Enterprise Readiness
API Authentication & Authorization
Data Isolation
Query Audit Logging
Secure Model Inference
Compliance Support
Integrations
6 total apps
OG
Direct integration with GPT-3.5 and GPT-4 for query execution
AC
Support for Claude models with native LMQL compatibility
HF
Integration with open-source LLM models from Hugging Face
DW
Direct connectors to Snowflake, BigQuery, and Redshift
P&
Native libraries for programmatic query execution
RA
Full REST API for integration with custom applications
Virtual Delivery Center · A new delivery category
A Virtual Delivery Center for
LMQL
Pre-vetted experts and AI agents in the loop, assembled as a delivery
pod. Pay in Delivery Units — universal pricing across roles,
seniority, and tech stacks. No hiring, no contracting, no procurement
cycle.
Plans from $2,000 — Starter Pack, 10 Delivery Units, 90 days
Refundable on unused Delivery Units, anytime — no questions asked
Re-delivery guarantee on acceptance miss
Pre-flight delivery sizing — you see the plan before you commit
What is LMQL and how does it differ from traditional prompt engineering?
LMQL is a declarative query language that abstracts away complex prompt engineering. Instead of hand-crafting prompts, you write SQL-like queries. AiDOOS handles the LLM interactions, optimization, and cost management automatically.
Which language models does LMQL support?
LMQL supports OpenAI's GPT models, Anthropic Claude, and open-source models from Hugging Face. AiDOOS provides unified access and cost optimization across all integrated models.
How does AiDOOS enhance LMQL deployment?
AiDOOS provides managed infrastructure, enterprise governance, audit logging, cost optimization, and integration capabilities. Organizations avoid managing underlying LLM APIs while maintaining full control and compliance.
Can LMQL integrate with existing data warehouses?
Yes. LMQL connects directly to Snowflake, BigQuery, Redshift, and other enterprise data warehouses. AiDOOS manages the integration pipelines and ensures secure data flow.
What are typical cost savings with LMQL and AiDOOS?
Organizations typically see 30-40% cost reduction through intelligent token caching, batch processing optimization, and model selection. AiDOOS continuously monitors and optimizes LLM usage automatically.
Is LMQL suitable for production use?
Yes. LMQL with AiDOOS governance provides enterprise-grade reliability, audit trails, SLAs, and security certifications required for production AI applications.
Real results from enterprises deployed through AiDOOS
Enterprise Data Analytics Firm
"LMQL reduced our document processing pipeline development time from 6 months to 2 weeks, while AiDOOS managed scaling and cost optimization seamlessly."
— Chief Data Officer
Financial Services Organization
"We leveraged LMQL to analyze thousands of compliance documents daily. AiDOOS governance features ensured audit-ready operations and 35% cost reduction."
— Head of AI Operations
SaaS Analytics Platform
"LMQL enabled us to ship AI-powered customer insights as a core product feature without building custom ML infrastructure."
— Product Manager
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