Question answered on this page: How can an AI development agency find companies asking for LLM, RAG, agent, or workflow-automation work?
Technology use case / AI and LLM
How can an AI development agency find companies asking for LLM, RAG, agent, or workflow-automation work?
Turn “AI” into a delivery-specific evidence test.
Leadiy matches explicit AI delivery signals—such as LLM integrations, RAG, agents, vector search, and validated AI stack combinations—rather than treating every mention of “AI” as a qualified buyer.
Evidence / AI specificity ladder
The signal becomes stronger as the requested outcome becomes testable.
This ladder does not score commercial value. It records how much delivery evidence the source actually provides.
AI specificity ladder
Source-bound / no invented certainty
A deliverable and technical system are named
Examples include RAG over a defined corpus, an agent with tools, vector search, an LLM integration, or a workflow automation with system boundaries.
A validated stack appears together
A complete combination such as Python/FastAPI with OpenAI and pgvector must contain the relevant parts—not one broad keyword.
The source mentions AI without an owned outcome
Keep the signal unqualified until the source supplies delivery scope, evidence, or a relevant service need.
Workflow / in order
Qualify the system that must work after the demo.
An AI brief becomes actionable when the agency can identify the input, output, operating boundary, and accountable result.
Choose a real capability
Select the AI systems and complete stacks the team can deliver, operate, and support.
Find the owned outcome
Read for a business process, data source, user action, integration, reliability requirement, or other concrete finish line.
Reject the adjective
If “AI-powered” is the only evidence, do not promote it into an implementation lead.
Sources / inspect directly
Evidence routes that own the underlying claims.
The intent page explains a decision. Methodology and data pages retain authority for definitions and aggregates.
- Leadiy sourceAI / LLM data page
- Leadiy sourceTechnology matching
- Leadiy sourcePublic methodology
Shared public contract
Definitions and limits do not change from page to page.
The methodology defines opportunity, vacancy, and lead; source handling; stable-identity deduplication; update cadence; technology matching; suppression; privacy; and known limitations.
Read the methodologyWhat this page refuses to claim.
- An AI or LLM mention is not proof of budget, readiness, or purchasing authority.
- Technology labels describe normalized evidence and can overlap.
- No trend claim belongs here without the methodology’s required baseline.
- Aggregate budgets must not be cited while material outliers remain unresolved or unmarked.
Match the system you can operate, not the trend you can name.
Inspect the AI/LLM dataset for public aggregate evidence, then use product matching for the agency’s own delivery profile.