Praesera Pre-release enquiries

The Praesera workspace

Govern AI systems as connected operational work.

Praesera is a private, pre-release desktop workspace for AI governance leads, managers, risk managers, DPOs, internal auditors and consultants. It supports recording AI systems, connecting risks to controls and evidence, documenting assessments and decisions, and following actions over time.

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Active pre-release development Connected•Operational•Traceable
Praesera — Operational AI GovernanceDESKTOP WORKSPACE
Praesera desktop workspace showing current system oversight, review work and outstanding actions
Review systems, upcoming reviews and outstanding actionsCurrent pre-release workspace
System of recordAI System Register
Operational chainRisk → Control → Evidence → Action
PersistenceNative local SQLite
Governance historyHuman-readable audit events

REAL GOVERNANCE WORK SESSION

Review one AI system. Understand the work around it.

Praesera begins with an AI system rather than an isolated assessment. Review its purpose, ownership and current governance position, examine the connected risks, controls and evidence, then understand what decisions have already been made and what work still requires attention.

  1. 01

    Open an AI System record.

    Understand its purpose, ownership and governance context before beginning review.

  2. 02

    Review connected governance work.

    See linked risks, controls, evidence and assessments together.

  3. 03

    Identify what happens next.

    Record decisions, assign follow-up and continue the work over time.

Praesera AI System Register showing an AI system record and its governance context
Example work session: review one AI system and understand its current governance position.

Current product scope

A connected record for AI governance work.

The current workspace brings together systems, assessments, risks, controls, evidence and actions so professionals can review a governance position and follow the work that remains.

AI

AI System Register

Inventory references, purpose, ownership, lifecycle, provider context, human oversight, internal risk and review dates.

Operational inventory
AS

Assessments

Structured governance review records that can connect back to systems, evidence, actions and future framework requirements.

Assessment foundation
RSK

Risk Register

Internal qualitative risk analysis, treatment, ownership, residual position and review management without pretending to make a statutory classification.

Internal methodology
CTL

Controls

Implementation status, operating status, review dates and direct relationships to systems, risks, evidence and actions.

Control lifecycle
EVD

Evidence

Evidence metadata, source, custodian, review/expiry state and links to the work that the evidence supports.

Evidence lifecycle
ACT

Actions

Remediation owners, priority, due dates, linked records, completion notes and activity history.

Work queue

REAL GOVERNANCE WORK SESSION

Review one AI system. Understand the work around it.

Open one AI system and begin with its purpose, ownership and governance context. Review the risks connected to it, examine the controls and evidence that support the current position, then identify what remains unresolved. Praesera keeps the working context together so the next decision and follow-up are clear.

01
Open the AI system record

Understand its purpose, ownership and governance context before beginning review.

02
Review connected governance work

See linked risks, controls, evidence and assessments together.

03
Identify what happens next

Record decisions, assign follow-up and continue the work over time.

Praesera AI System Register desktop interface
A system record brings its purpose, connected governance work and next action into one working context.

Local-first foundation

Local-first storage with explicit limitations.

The current product stores governance records locally and treats storage, migrations, audit history and known limitations as explicit engineering concerns.

Current limitation: database encryption at rest, enterprise identity/RBAC, cloud sync and cryptographic audit sealing are not yet implemented in the pre-release product.
ImplementedNative SQLite persistence

Operational records survive application restart and are stored through the Tauri-native persistence layer.

ImplementedVersioned migrations

The native data layer maintains schema metadata and migration history rather than silently replacing data.

ImplementedTyped repository boundary

The user interface depends on domain/repository contracts rather than talking directly to the database.

Deliberate future workEnterprise security layers

Encryption, key management, RBAC, managed backup and multi-user architecture will be implemented only when properly designed and tested.

Future framework architecture

Future framework support should remain traceable to its source.

Framework mappings are future work. They will be developed against authoritative material with source, version and requirement relationships kept visible rather than inferred automatically.

No automatic compliance verdicts. Praesera is not designed to convert a completed checklist into a claim that an organisation is legally compliant.
Planned source layer

EU AI Act

Future requirement and provenance architecture tied to operational records.

Planned source layer

NIST AI RMF

Future relationship between risk-management concepts and organisational governance work.

Planned source layer

ISO/IEC 42001

Future management-system alignment without implying certification.

Planned jurisdiction layer

UK AI Governance

Future UK-specific guidance and regulatory-source architecture.

Development transparency

What exists now and what remains future work.

Praesera is under active development. The current product scope is shown separately from planned framework support, interface hardening, professional review and broader deployment.

Current
Operational GRC backbone

AI System Register, connected Risks, Controls, Evidence and Actions, native local persistence, migrations and audit events.

Next
Responsive desktop GUI hardening

Improving workspace layout, tables, forms, relationship controls and behaviour across realistic desktop window sizes.

Later
Source-verified governance frameworks

Framework provenance, versioning and requirement relationships, developed deliberately rather than inferred automatically.

Future
Professional review and broader deployment

Specialist evaluation, Windows QA, packaging, security hardening and future commercial deployment stages.

Praesera Insights whitepaper on operational AI governance

Praesera Insights

AI Governance Is Not a Policy

Our working paper examines the operational gap between governance intent and the evidence, controls, responsibilities and actions needed to demonstrate how an AI system is governed in practice.

Free PDF · No registration required

Read the perspective

Praesera

Discuss a governance workflow or provide practitioner feedback.

Use the contact link for product, practitioner or future commercial enquiries.

info@praesera.com