High Selectivity Opportunity Engine
Semantic commercial discovery and qualification
A human-directed, machine-enabled system for converting unstructured market signals into semantically interpreted, evidence-supported commercial opportunities.
Index
01 · Premise
From market signal to commercial opportunity
The High Selectivity Opportunity Engine is designed around a simple problem: useful commercial opportunities are often not described in the same language as the resources capable of performing the work.
Instead of relying primarily on job titles or keyword matching, the system interprets observable market evidence, identifies the underlying buyer need and work unit, maps that work against documented capabilities and constraints, and persists qualified opportunities as structured records.
Commercial objective
“I need work.”
The engine exists to turn that human intent into a disciplined commercial discovery process without allowing search volume, keyword coincidence, or machine confidence to replace evidence.
02 · System Spine
Interpret before matching
The system is not merely searching jobs. It converts unstructured market evidence into a compact commercial model and then reasons across the relationships in that model.
- Market Signal
- Semantic Interpretation
- Entity + Relationship Extraction
- Ontological Representation
- Commercial Qualification
- Structured Persistence
- Human Action
The system is not primarily asking
“Does this posting contain the right keywords?”
It is asking
“What is this buyer actually trying to accomplish, and is there a documented resource capable of doing it?”
03 · Commercial Ontology
A small operational model
The ontology is intentionally compact. It identifies the things that must exist for a commercial opportunity to be represented without collapsing buyer, need, work, evidence, resource, and commercial state into one undifferentiated record.
- Resource
- Capability
- Buyer
- Need
- Work Unit
- Opportunity
- Contact
- Organization
- Source
- Evidence
- Constraint
- Timing
- Commercial State
- Action
- Outcome
What the delivery resource can credibly perform.
What the commercial actor is trying to accomplish or resolve.
The concrete work implied by the buyer need.
The bridge between market demand and documented ability.
The source material that justifies the commercial interpretation.
The current evidence-supported stage of the commercial record.
What happened after human commercial action.
How new evidence changes the persistent opportunity record.
04 · Qualification
Evidence before enthusiasm
A market signal does not become an opportunity simply because the work sounds relevant. The engine tests whether the implied commercial relationship is actually practical.
- Remote Compatibility
- Geography
- Availability
- Rate
- Autonomy
- Timing
- Contact Path
- Commercial Practicality
- Capability Match
- Evidence Quality
Commercial state progresses only as evidence supports it
- Partial Contact
- Contact
- Qualified Contact
- Lead
- Opportunity
05 · Opportunity Record
Structured persistence
Each qualified opportunity becomes a durable machine-readable record rather than remaining trapped inside a search result, posting, message, or conversation.
Buyer, organization, need, work unit, resource, capability, contact, source, action, and outcome.
Explicit mappings between buyer need, required work, resource capability, evidence, constraints, and commercial state.
Observable source material supporting the interpretation and qualification decision.
Delivery, geography, availability, rate, autonomy, timing, contact path, and commercial practicality.
The current commercial classification and next action supported by the available evidence.
The source and evidentiary lineage remain attached as the record is reviewed, acted upon, and updated.
The persistent opportunity ledger becomes the shared system of record. It preserves what was observed, what was inferred, why the opportunity qualified, what action was taken, and what happened next.
06 · Current State
Active system design and implementation
The current implementation is being developed as a practical commercial system rather than as a general-purpose ontology. Its purpose is to improve the quality of opportunity discovery, qualification, persistence, and follow-through.
Human review remains the decision point for application, outreach, proposal, negotiation, and other commercial action. The machine-facing model structures evidence and relationships; it does not replace commercial judgment.
Observed outcomes return to the record. A response, rejection, qualification event, proposal, client conversion, or revenue event adds evidence and changes the commercial state of the opportunity.
Conceptual spine
Market signal → semantic interpretation → ontological mapping → commercial qualification → structured persistence → human action.