Capabilities

Capabilities for building the intelligence layer.

Stratir designs the connective layer between scattered sources, business questions, entity logic, agents, analyst review, and usable delivery.

SYSTEM DESIGN SURFACE

Requirement, source context, entity logic, and review gates stay connected from intake to delivery.

Source to decision

REVIEWABLE OPERATING MODEL

REQUIREMENT

SOURCE MAP

REVIEW LOOP

Requirement

Define the decision, user, risk, sensitivity, and evidence standard before tooling decisions are made.

Source fabric

Connect registries, open web, dark-web context, regional records, customer context, and selectors.

Ontology

Represent people, companies, documents, events, sources, and findings as reusable connected objects.

Agent layer

Use bounded agents to collect, enrich, compare, summarize, test, and QA without removing review.

Review system

Preserve provenance, uncertainty, source quality, analyst judgment, and delivery readiness.

Six capability pillars, one intelligence layer.

These are not steps in a cycle. They are the categories Stratir can design, build, combine, or transfer depending on what the business needs to know and operate.

Data foundation

All-source aggregation systems

Build investigation surfaces that unify selectors, registries, business records, open-source traces, identity signals, and dark-web context into structured evidence.

Feynman proof of work, CPF/CNPJ pivots, KYB registry paths, AML research, selector lookup, source normalization.

Knowledge model

Ontology and entity resolution

Turn people, companies, selectors, documents, regions, transactions, sources, and findings into connected objects teams can search, review, and reuse.

Entity resolution, relationship mapping, case memory, source history, evidence lineage, graph-ready data models.

Market context

Regional and business intelligence

Design research workflows around geography, jurisdiction, language, registry access, business context, and fragmented data environments.

LATAM, Singapore, Hong Kong, trade finance, registry-aware operating contexts, counterparty research.

Controlled research

OPSEC-aware collection design

Support sensitive research where collection posture, source handling, controlled pivots, and low-noise workflows matter as much as speed.

Quiet-mode research, OPSEC posture, controlled collection discipline, sensitive-source handling, review gates.

Intelligence Layer

One connected surface for the moving parts.

Sources, objects, agents, and review gates stay connected so the system remains inspectable.

SourcesObjectsAgentsReview

Execution systems

Agentic engineering and automation

Build agents and software workflows that assist research, enrichment, engineering, QA, and synthesis while preserving human review and local verification.

Codex, Cursor, Hermes, Pi.dev, security review, local verification loops, analyst-in-the-loop automation.

Adoption layer

Training and tradecraft transfer

Turn intelligence methodology into repeatable training, playbooks, and operating habits for analysts, investigators, founders, and internal teams.

OSINT, CTI, DarkNet, OPSEC, multilingual learning paths, analyst enablement, internal tradecraft programs.

The work decides which pillars matter.

Some teams need registry-heavy entity resolution. Others need controlled research, automation, training, or a complete operating layer.

Research operations

Build the internal layer for recurring investigations, due diligence, casework, and source-backed decision support.

Risk and fraud workflows

Structure evidence around counterparties, impersonation, illicit finance, exposed entities, suspicious infrastructure, and reviewable leads.

Regional intelligence

Stand up workflows for jurisdictions where records, languages, registries, source quality, and operating context vary heavily.

Agent-assisted execution

Deploy agents for collection, enrichment, engineering, QA, synthesis, monitoring, and reporting with human control built in.

Tradecraft transfer

Turn the system into training, playbooks, review standards, and repeatable practice so teams can keep using it.

Useful when a team needs the intelligence layer, not another isolated tool.

Source-backed due diligence, KYB, and entity research systems.

AML, fraud, and counterparty review workflows with evidence trails.

Impersonation mapping, public-risk research, and case-building support.

Dark-web, fringe-source, and exposed-infrastructure monitoring.

Internal intelligence layers for research, security, risk, and operations teams.

Training programs, playbooks, and review standards that transfer the tradecraft.

Discuss system design