One Platform. Three Levels of Intent and Control.
Improve. Standardize. Control.
Preflight
Improve the question.
At the input layer.Teams
Standardize the question.
At the workflow layer.Atticus
Control the environment in which the question is answered.
At the infrastructure layer.VertixIQ Preflight
Improve the question.
For professionals, freelancers, and SMBs using AI daily.
Works with any AI.
Improve your prompt here, use it in ChatGPT, Claude, Gemini, Copilot — whatever you prefer.
Catch what you didn’t know was missing.
Unstated assumptions, vague instructions, missing jurisdiction, undefined scope — the gaps that lead to fabricated details and unreliable output.
Get the response you actually meant to ask for.
Better specificity and structure turn “close enough” into “exactly what you meant.”
VertixIQ Teams
Standardize the question.
For cross-functional teams that need to control how AI operates across their organization — not at the prompt level, but at the API and workflow layer.
AI use moves from individual behavior to institutional standard.
Who It Is For
Teams, departments, and organizations where multiple systems, workflows, or people interact with AI — and the organization needs to define the rules once, not per person.
One source of truth across the organization.
A shared, immutable knowledge base that every AI interaction draws from — so sales, legal, and ops are all operating against the same facts, regardless of which tool or integration is calling the model.
Standardized behavior at the API layer.
Templates, guardrails, and output standards are enforced before the model sees the request — not after. The rules live in infrastructure, not in individual judgment.
Visibility into how AI is being used.
What is being requested, by which systems, how often, and where output quality is breaking down — across every integration point, not just a chat window.
VertixIQ Atticus
Control the environment in which the question is answered.
Intent governance for regulated markets.
Who It Is For
Organizations operating under legal, regulatory, or fiduciary obligation — where AI-generated output carries consequences. Financial institutions, law firms, healthcare systems, government agencies, and compliance-driven enterprises.
AI-generated claims validated against defined source authority.
Outputs are checked against regulatory filings, internal policies, and source documents before output is accepted. Nothing is asserted without citation. Nothing passes without verification.
System-integrated across your existing infrastructure.
SharePoint, Google Drive, CRMs, ERPs, knowledge graphs — Atticus operates within your environment, enforcing governance at the point of execution.
Audit-grade traceability on every interaction.
Full chain of custody — what was prompted, what sources were cited, what was flagged as uncertain, and what was escalated for human review. Every AI execution produces a defensible record.
Multi-layered compliance architecture.
Five enforcement layers — prompt, definition, code, validation, and human oversight — designed so no single layer carries the full burden of control. Built to satisfy GDPR, EU AI Act, and NIST AI RMF requirements.
| Preflight | Teams | Atticus | |
|---|---|---|---|
| Character | Light. Stateless. User-level. | Shared context. API-layer standardization. | Connected. Stateful. System-integrated. |
| Knowledge | Personal context | Shared structured knowledge | Institutional knowledge graph |
| State | None | Shared across team | Persistent across sessions and systems |
| Integration | None | Light | SharePoint, Google Drive, CRMs, ERPs, APIs |
| Intent | Input improvement | Process standardization | Intent governance with audit trail |
| Audience | Professionals, freelancers, SMBs | Cross-functional teams, departments | Regulated industries, institutions |
Preflight = personal precision. Teams = shared discipline. Atticus = institutional integrity.
Start with Preflight. Scale when you’re ready.
The platform grows with your needs — from individual precision to institutional governance.