An environment for inquiry - complete documentation
Veritheia is where you author your own understanding. Not through AI-generated summaries, but through structured engagement with your documents, guided by your questions, shaped by your framework. This guide explains what you can do with Veritheia and how it preserves your intellectual sovereignty.
Veritheia is a foundation for developing understanding through engagement with your documents. Think of it as infrastructure for your intellectual work—like a library that reorganizes itself around your specific questions. It’s not an AI that reads for you or generates insights on your behalf. Instead, it creates conditions where your insights can accumulate through your decision-making process at scale.
Think of Veritheia as a research assistant who never tells you what to think but helps organize your materials according to your questions, measures documents against your criteria, and preserves the trail of your developing understanding. The insights that accumulate through your decision-making process are irreducibly yours because they arise from your engagement with documents projected through your intellectual framework.
When you begin a research journey in Veritheia, you’re not asking AI to summarize papers. You’re creating a structured inquiry where AI measures documents against YOUR research questions, using YOUR definitions, within YOUR theoretical framework.
Your framework is your intellectual stance—the lens through which you view documents. It consists of:
Research Questions: The specific questions driving your inquiry. Not generic topics but precise questions like “How are large language models being utilized for cybersecurity threat detection in enterprise environments?”
Key Definitions: Your understanding of important terms. When you define “contextualized AI” as “systems that leverage domain-specific, proprietary knowledge,” every document gets measured against YOUR definition, not Wikipedia’s.
Assessment Criteria: What makes a document relevant or valuable to you. Perhaps relevance means directly addressing your research question with empirical evidence. Perhaps contribution means providing novel methodology you haven’t seen before.
Theoretical Orientation: Your intellectual perspective. Are you approaching this from a post-industrial computing lens? A critical theory perspective? A pragmatic engineering stance? This orientation shapes how documents are understood within your journey.
Once you’ve defined your framework, something remarkable happens: documents stop existing generically. They become projected through your framework, creating a unique view that didn’t exist before.
The same academic paper means something entirely different when projected through a computer scientist’s framework focused on algorithms versus a psychologist’s framework focused on human cognition. In Veritheia, both projections can exist simultaneously without conflict because each exists within its own journey space.
This projection isn’t just tagging or filtering. The system:
With documents projected through your framework, engagement becomes tractable even at scale. Instead of facing 3,000 papers as an undifferentiated mass, you encounter:
Relevance Landscapes: Documents arranged by how well they address your specific questions. Not “important” papers but papers important to YOUR inquiry.
Contribution Patterns: Clusters of documents that contribute similar insights, helping you recognize schools of thought, methodological approaches, or theoretical camps.
Conceptual Bridges: Connections between documents that share your vocabulary, even if they come from different fields or use different terminology in their original form.
You engage with these projections by:
Your framework isn’t a static filter—it’s a living intellectual stance that evolves through engagement with documents.
Start with what you know:
The framework doesn’t need to be perfect or complete. It needs to be yours—an authentic expression of your current understanding and interests.
As you engage with documents, patterns emerge that refine your framework:
Vocabulary Evolution: You encounter terms that better express your concepts, or discover that what you called one thing is actually several distinct ideas.
Question Sharpening: Broad questions naturally divide into specific sub-questions. “How do LLMs enhance security?” becomes “How do LLMs detect anomalies?” and “How do LLMs generate security policies?” and “How do LLMs assist incident response?”
Criteria Clarification: Your sense of what’s valuable becomes more precise. “Relevant” evolves from “mentions LLMs and security” to “provides empirical evaluation of LLM-based threat detection with industry-standard benchmarks.”
Theoretical Development: Your perspective deepens through encounter with diverse approaches, potentially synthesizing elements from multiple schools of thought into your unique stance.
Your framework in Veritheia is stored as structured data that can evolve:
Journey: "LLM Applications in Cybersecurity"
Framework Version: 3 (evolved from Version 2 after engaging with 500 documents)
Research Questions:
- Primary: "How do transformer-based models detect zero-day exploits?"
(evolved from: "How do LLMs detect threats?")
- Secondary: "What are the false positive rates in production deployments?"
(added after recognizing this gap in literature)
Vocabulary:
- "Contextualized AI": "Models fine-tuned on proprietary security logs"
(refined from: "AI that knows about security")
- "Zero-day detection": "Identifying exploits without prior signatures"
(added after encountering this concept repeatedly)
Assessment Criteria:
- Relevance: Must include empirical evaluation (not just proposals)
- Contribution: Must report actual deployment results (not just experiments)
(both criteria sharpened from initial "about LLMs and security")
Formation is what happens when you develop understanding through structured engagement with sources. In Veritheia, formation is never given to you—it emerges from your journey.
Formation manifests as:
Accumulated Insights: Not a list of facts but developing understanding. The recognition that “all successful LLM security implementations share these three characteristics” emerges from your engagement with hundreds of implementations.
Pattern Recognition: The ability to see connections others might miss because you’ve engaged with documents through your unique framework. You notice that papers from industrial labs focus on deployment challenges while academic papers focus on novel architectures—a pattern visible only through your projection.
Theoretical Development: Your framework itself becomes more sophisticated. You started investigating “LLMs in security” but developed a nuanced understanding of “the role of transformer attention mechanisms in anomaly detection within high-noise environments.”
Methodological Confidence: You don’t just know what the literature says—you know how to navigate literature in your domain. This meta-knowledge, this scholarly muscle memory, is perhaps the deepest form of formation.
In Veritheia, you write your formation into existence through:
Decision Rationales: When you exclude a paper, you write why. These rationales reveal your developing judgment. Early in your journey, you might exclude papers for surface reasons. Later, your exclusions show sophisticated understanding of methodological limitations or theoretical incompatibilities.
Synthesis Passages: You write connections between documents, creating bridges that exist nowhere else. “Paper A’s approach to feature extraction could address Paper B’s scalability challenges, though neither author makes this connection” is insight that emerges from your unique perspective.
Framework Evolution Notes: You document why your framework changed. “I initially separated ‘detection’ and ‘prevention’ as distinct categories, but the literature reveals these are intertwined in ways that make separation artificial” shows intellectual growth.
Reflection Entries: You write about your developing understanding. “I’m beginning to see that the field’s focus on accuracy metrics obscures the more important question of deployment feasibility” captures formation in process.
Formation in Veritheia is cumulative and personal:
Cumulative: Each journey builds on previous journeys. Your second literature review benefits from the scholarly capacity developed in your first. Your tenth investigation operates at a level of sophistication impossible in your first.
Personal: Your formation reflects your unique path through knowledge. Two researchers investigating the same topic with access to the same documents will develop different formations because their journeys—their questions, their frameworks, their engagement patterns—differ.
Non-transferable: Someone can read your synthesis, study your framework, even follow your exact process, but they cannot acquire your formation. Formation comes from the journey itself, not from its outputs.
Veritheia supports various types of intellectual journeys, each with its own pattern of formation:
For comprehensive analysis of research literature:
You define research questions that scope your investigation, provide precise definitions of key terms, establish inclusion/exclusion criteria, and set assessment thresholds. The system projects thousands of papers through this framework, measuring each against your criteria.
Your formation results from your structured engagement with systematically assessed papers, making reasoned inclusion decisions, writing synthesis that connects patterns, and developing theoretical understanding. The outcome is not just a literature review but enhanced capacity for scholarly work.
For teachers developing and evaluating student work:
You define learning objectives that guide assessment, create rubrics that reflect your pedagogical values, establish safety constraints appropriate for your students, and set evaluation criteria that encourage growth. The system projects student work through this framework, providing consistent assessment while flagging edge cases.
Your formation emerges through recognizing patterns in student development, refining rubrics based on actual student work, developing intuition for productive constraints, and building pedagogical expertise. Both you and your students develop through the journey.
For investigating new domains without fixed frameworks:
You begin with curiosity rather than rigid questions, allow vocabulary to develop through engagement, let criteria evolve through encounter, and embrace framework evolution as discovery. The system supports this exploration by enabling rapid framework adjustment and surfacing potential connections for your review.
Your formation accumulates as your wandering becomes purposeful through your decision-making process, questions that sharpen through encounter, vocabulary that crystallizes through use, and understanding that surprises you. The journey’s value lies not in confirming hypotheses but in discovering what you didn’t know to ask.
For connecting knowledge across fields:
You maintain multiple conceptual vocabularies, create bridges between different literatures, recognize patterns across domains, and synthesize diverse perspectives. The system enables this by supporting multiple projection frameworks and surfacing potential conceptual overlaps for your review.
Your formation accumulates through your decision-making process as you identify connections others miss, develop hybrid vocabulary, create novel theoretical syntheses, and build integrative understanding. You become a translator between worlds, creating knowledge that exists at intersections.
Your work in Veritheia remains yours in the deepest sense:
Privacy isn’t a policy overlay but an architectural foundation:
Partition Boundaries: Your data lives in your partition, isolated at the database level. Queries cannot cross partition boundaries without explicit authorization.
Journey Isolation: Even within your partition, journeys remain separate. Documents projected in one journey don’t affect projections in another unless you explicitly connect them.
No Surveillance: The system cannot analyze patterns across users, generate recommendations from collective behavior, or mine insights from aggregate data. The architecture prevents surveillance, not policy.
Your intellectual work remains sovereign:
Your Frameworks: The research questions, definitions, and criteria you create are your intellectual property. They represent your unique scholarly perspective.
Your Formations: The insights that emerge from your journeys cannot be extracted or transferred. They exist only in context of the journey that created them.
Your Syntheses: The connections you write between documents, the patterns you recognize, the understanding you develop—these are authored by you, not generated by AI.
When you choose to share, you control what and how:
Selective Sharing: Share specific journeys or journals while keeping others private. Share methods while keeping results private. Share frameworks while keeping formation sovereign.
Revocable Access: Permissions can be withdrawn. Shared content can be unshared. Bridges can be burned.
Attribution Preservation: Shared content maintains clear attribution chains. Your intellectual lineage is preserved.
Run multiple related journeys simultaneously:
Each maintains its own projection while you can see connections across journeys.
While formation remains personal, collaboration is possible:
Begin with something meaningful but manageable:
Veritheia is currently in active development. The system is being built as open-source infrastructure (MIT licensed) that institutions and individuals can deploy.
For Researchers and Educators (Coming Soon):
For Developers (Available Now): You can run Veritheia locally:
git clone https://github.com/zipthought/veritheia.git
cd veritheia
dotnet build
dotnet run --project veritheia.AppHost
https://localhost:5001 in your browserhttps://localhost:15888If you’re a researcher or educator:
If you’re a developer:
For technical setup details, see the root README. For contributing, review the Documentation Guide.
AI summarization gives you processed output. Veritheia gives you structured engagement. You read documents, make decisions, write connections, and develop understanding. AI measures and organizes but never concludes.
Start with provisional frameworks. Your first research question might be “What are people saying about X?” Your vocabulary might be basic. Your criteria might be simple. The framework evolves through engagement—that’s part of formation.
Absolutely. Framework evolution is expected and tracked. Each version is preserved, allowing you to see how your understanding developed. Documents can be re-projected through evolved frameworks.
You verify through engagement. The AI’s assessments are measurements, not truths. Through reviewing assessed documents, you calibrate your framework and develop intuition for the system’s strengths and limitations.
You can override assessments, refine criteria, or adjust frameworks. Misassessment often reveals framework ambiguity that, once clarified, improves future assessments. The system applies your refined frameworks to subsequent processing.
Veritheia invites you to reclaim your intellectual sovereignty—to develop understanding through engagement rather than consumption. Every journey you undertake builds your formation, your accumulated capacity for intellectual work.
Bring your questions. Trust the process. Author your understanding.
Formation awaits. It begins with your first question.
This guide reflects Veritheia’s core principle: you are the author of your understanding. The system provides structure and scale, but the insights that emerge are irreducibly yours.