Products / Intelligence Platform
AI research & decision support

EVA Defense Intelligence Platform

A secure AI research and decision-support layer for defense knowledge — built to search controlled institutional knowledge, synthesize evidence at scale, analyze alternatives and uncertainty, and brief human-reviewed outputs.

01 // SEARCH

Controlled institutional knowledge
Retrieval across public, licensed, and customer-provided repositories.

02 // SYNTHESIZE

Evidence at scale
Combine sources into a coherent, sourced picture.

03 // ANALYZE

Alternatives & uncertainty
Surface competing explanations, not one collapsed answer.

04 // BRIEF

Human-reviewed outputs
Export to standard briefing and memo formats.
Built around the Department's AI direction

An institutional AI layer, not another standalone chatbot.

CDAO publicly emphasizes decision advantage, enterprise agents, interoperable data access, and rapid AI adoption. EVA is positioned to fit inside that direction rather than compete with it.

Pentagon-oriented use cases

High-value knowledge work that benefits from secure retrieval.

Synthesis and traceability, across four recurring categories of institutional knowledge work.

Policy & strategy

Compare doctrine, policy, history, and competing interpretations.

Acquisition

Summarize requirements, market research, and program knowledge.

Lessons learned

Extract recurring findings across reports and archives.

Education

PME, staff training, reading lists, and case studies.

Reference architecture

Permission-aware retrieval and auditability are product requirements, not add-ons.

Layer 1

Controlled data
Public, licensed, and customer-provided repositories.

Layer 2

Access layer
Identity, RBAC/ABAC, classification, and need-to-know policies.

Layer 3

EVA core
Retrieval, synthesis, domain models, and workflow agents.

Layer 4

Assurance
Citations, confidence, logging, evaluation, and human review.
Analyst workspace

Evidence before confidence.

Every substantive answer can link back to its supporting documents and passages. Sourced fact stays separate from model inference, interpretation, and unresolved uncertainty.

Competing explanations are shown instead of collapsed into a single answer — analysts pin evidence, build timelines, compare sources, and export human-reviewed briefs.

Cited

Source-grounded output

Logged

Query & edit provenance
Structured red-team & alternative-analysis workflows

Designed to challenge assumptions without automating consequential decisions.

Generate alternative hypotheses from the same evidence set.
Identify assumptions, missing evidence, and information that would change the assessment.
Compare historical analogies and explicitly state where the analogy breaks down.
Create argument maps showing evidence for and against competing interpretations.
Run pre-mortem and devil's-advocate exercises for policy, acquisition, and organizational decisions.
Require human approval before any analytical product is treated as an institutional conclusion.
Security and authorization roadmap

What's being built, stated plainly as a roadmap.

Important
These are product requirements and roadmap items — not claims of current certification. Authorization status should be confirmed directly with Eva Defense before any procurement or deployment decision.
Zero trust
Identity-centric access, least privilege, and continuous verification.
Data separation
Tenant, repository, and policy boundaries.
Encryption
Data in transit and at rest.
Audit logging
User, retrieval, model, and administrative events.
Responsible AI & TEVV

Built into the product lifecycle, not bolted on after.

DoD’s RAI pathway emphasizes traceability, auditability, risk analysis, and forensics; CDAO also publishes AI test-and-evaluation frameworks. These practices reflect that direction.

Model T&E and data/algorithm quality practices above describe the intended lifecycle approach; they are not a substitute for sponsor-specific authorization or independent evaluation.

Integration strategy

Fit into the ecosystem — the commercial advantage is modularity.

EVA connects to existing repositories, identity systems, and approved model infrastructure rather than replacing them.

API-first retrieval and agent interfaces.
Pluggable model layer so approved models can be swapped or compared.
Connectors for document repositories and structured data sources.
Permission-aware retrieval that respects source-system access controls.
Export to standard briefing, memo, and research formats.
Design for modular acquisition and interoperability rather than vendor lock-in.
Development path

From frozen suppliers to production release.

01
Bound
Choose one unclassified/CUI-appropriate corpus and user group.
02
Ingest
Index approved sources with provenance and access controls.
03
Evaluate
Build mission-specific accuracy and citation benchmarks.
04
Pilot
Run research and briefing workflows with human reviewers.
Why EVA

Turn defense knowledge into decision advantage.

EVA is designed to help defense organizations search, understand, challenge, and brief their knowledge faster — while preserving evidence, permissions, auditability, and human authority.
Private
Customer-controlled
Grounded
Evidence-linked
Modular
Interoperable
Human-led
Authority preserved