Enterprise AI governance · Emerging technology

Govern what’s next.

Quantum AI Strategy Group provides visibility, governance, assurance, and intelligence for enterprise AI and emerging technology, so organizations can move from AI assumptions to evidence.

In production
QWatch · QComp
In development
QERA · QCode · QScale
Advisory
Strategy · Governance · Security
Enterprise AI telemetry flowing through QAISG governance Identities, devices, browsers, AI platforms and network telemetry feed a governance layer that produces policy decisions, actions through enterprise controls, and evidence. Identities Devices Browsers AI platforms Network Discover Attribute Assess Govern Policy decisions Enterprise controls Evidence & reporting TELEMETRY SOURCES GOVERNANCE LAYER GOVERNED OUTCOMES

01 The market problem

AI adoption has outpaced enterprise visibility.

Assistants in browsers, copilots in productivity suites, models called from scripts, and agents acting on behalf of people arrived faster than the governance to observe them. Most organizations can describe their AI policy. Far fewer can show what is actually happening.

The result is a widening gap between adoption and governance. Closing it starts with answering a handful of concrete questions with evidence rather than assumptions.

  1. 01

    Which AI tools are actually being used?

    Discovery across identity, endpoint, browser, platform, and network telemetry.

  2. 02

    Who is using them, and in which parts of the business?

    Attribution to identities, groups, and business units.

  3. 03

    Which devices and identities are involved?

    Device and identity context for every observed interaction.

  4. 04

    How is AI interacting with enterprise systems?

    Observed connections between AI tools and enterprise platforms, integrations, and identities, with sensitivity indicators from integrated controls.

  5. 05

    Can governance teams produce evidence of controls and activity?

    Attributable, time-stamped records tied to policy and controls.

  6. 06

    Which AI tools are affected by a published vulnerability or provider incident, and can we contain them?

    Public advisories matched to observed AI tools, and scoped, approved containment through existing controls.

02 What QAISG does

Visibility leads to governance. Governance produces evidence. Evidence enables scale.

Four connected disciplines, applied in order, form the operating philosophy behind every QAISG platform and engagement.

  1. Visibility

    01 Discover

    Establish an evidence-based inventory of AI tools, models, and services, attributed to the identities and devices using them.

  2. Governance

    02 Govern

    Apply policy through decisions, approvals, and exceptions, enforced by the enterprise controls already in place.

  3. Assurance

    03 Evidence

    Produce attributable records that connect activity, controls, and outcomes to the frameworks that require them.

  4. Readiness

    04 Enable

    Use that foundation to adopt AI, agents, and emerging technology responsibly and at scale.

03 Featured platform

QWatch

Available

You cannot govern AI you cannot see.

QWatch is an enterprise AI visibility, threat intelligence, governance, and containment platform. It establishes an evidence-based picture of observed AI activity across identities, devices, browsers, IDE and desktop assistants, embedded AI, and native connectors, correlates it with published AI threat intelligence, and turns it into governed, verifiable outcomes.

Illustrative interface. Data shown is not from a customer environment.

Operating lifecycle

  1. Discover Detect AI tools and services across telemetry sources.
  2. Attribute Connect activity to identities, devices, and groups.
  3. Assess Evaluate observed activity against policy, sensitivity indicators, and published AI threat advisories.
  4. Govern Apply sanction, restrict, and block decisions with approvals and exceptions.
  5. Contain Propose, approve, and apply scoped containment through integrated controls; verify, then restore.
  6. Evidence Report activity, decisions, containment, and control effectiveness with provenance.

From visibility to intelligence and action

See what applies to you. Contain it with governance, not a blunt switch.

AI Threat Landscape

What is happening in AI security, which of it applies to your organization, and what to do next. QWatch draws on public intelligence and correlates it with the AI tools your telemetry shows in use.

  • CISA Known Exploited Vulnerabilities
  • NVD
  • OSV
  • AI provider status and advisories
  • Public sources, private results Queries to intelligence sources carry only QWatch’s global AI catalog identifiers. Your inventory, identities, and telemetry never leave your tenant; exposure is computed inside it.
  • Applicability, not inferred impact Each advisory is matched against your own observed activity and resolves to applies, potential exposure, or no matching activity recorded, and names any coverage gap. Nothing is inferred about data QWatch never collects.
  • From intelligence to action An applicable advisory can inform a containment proposal. Containment stays governed: permission-gated, approved, time-limited, and fully audited.

Governed Containment

When an organization needs to stop a specific AI tool, integration, or agent, QWatch provides a scoped, approved, reversible action executed through the controls it already operates, with evidence that it worked.

The AI kill-switch question

Boards, regulators, and security leaders are asking whether an organization can stop an AI capability when it needs to. A blanket switch is rarely the answer in an enterprise: it is unscoped, unapproved, and unverifiable. Governed containment answers the same question with precision: what exactly is contained, who approved it, which control enforced it, how we know it took effect, and when it is restored.

  • Detect Detect, assess, and alert only.
  • Approve QWatch proposes; an authorized person approves before anything is applied.
  • Auto-Contain Critical findings apply a pre-approved playbook automatically, only while every interlock holds: corroboration, tenant-validated thresholds, a healthy escalation channel, cooldowns, and daily limits. Automated actions restore themselves at expiry.
  • Shadow AI discovery

    Discover sanctioned, unsanctioned, and emerging AI usage from real telemetry: browsers, IDE and desktop assistants, embedded AI in business applications, and native connectors.

  • Identity attribution

    Attribute AI activity to identities, devices, and business units so usage becomes accountable, not anonymous. Individual-level analysis stays off by default.

  • AI threat intelligence

    Match published vulnerability and provider advisories to the AI tools observed in your environment. Exposure is computed inside your tenant and stated as applicability, not inferred impact.

  • Governed containment

    Propose, approve, and apply scoped, time-limited containment through the controls you already run. QWatch verifies in telemetry that the scope went quiet and tracks restoration.

  • Control effectiveness

    Continuously compare declared policy with observed activity and connector state. A control that is configured but not enforcing is flagged as ineffective, with the evidence.

  • Governance evidence

    Produce time-stamped, attributable records of observed AI activity, decisions, containment actions, and control outcomes for audits, boards, and regulators.

QWatch does not sit inline in network traffic. Enforcement is performed by the integrated enterprise security controls an organization already operates.

Metadata, not content. QWatch records the AI tool, timestamp, device, attributed identity, prompt length, and risk indicators. It never stores the text of prompts or responses, keystrokes, or screen contents.

Illustrative interface. Framework references are examples, not legal mappings.

04 Featured platform

QComp

Available

One control. Multiple frameworks.

QComp is a governance and compliance platform built around a Control Registry: a system of record for controls, framework mappings, evidence, assessments, and compliance activities. Define a control once and reuse it across every framework that requires it.

Control reuse

CONTROL · CTL-042 AI tool access is approved and reviewed 4 evidence items attached NIST AI RMF AI risk management ISO/IEC 42001 AI management systems ISO/IEC 27001 Information security SOC 2 Trust services criteria NIST CSF Cybersecurity framework EU AI Act Regulatory obligations

From framework to reporting

  1. Framework Select the frameworks and internal policies in scope.
  2. Requirement Decompose frameworks into specific requirements.
  3. Control Define or reuse controls that satisfy requirements.
  4. Evidence Collect and review evidence that controls operate.
  5. Assessment Assess effectiveness and track remediation.
  6. Reporting Report posture and gaps by framework and unit.

Supports mapping to

  • NIST AI RMF
  • ISO/IEC 42001
  • ISO/IEC 27001
  • SOC 2
  • NIST CSF
  • EU AI Act
  • Internal governance frameworks
  • Control Registry

    A single, versioned inventory of controls with owners, scope, implementation status, and test procedures.

  • Framework mapping

    Map each control to requirements across multiple frameworks, so one implementation satisfies many obligations.

  • Evidence management

    Attach, schedule, and review evidence against controls, with provenance and freshness tracked over time.

  • Assessments

    Run self-assessments, readiness reviews, and internal audits with consistent scoring and remediation tracking.

  • Reporting

    Report coverage, gaps, and evidence status by framework, business unit, or system to executives and auditors.

  • Governance workflow

    Coordinate reviews, approvals, exceptions, and remediation with a clear audit trail of who decided what and when.

QComp supports governance, evidence collection, framework mapping, and compliance programs. Compliance outcomes depend on how an organization designs, operates, and attests to its controls.

05 Platform portfolio

One portfolio for governing enterprise AI and what comes after it.

Two platforms in production today. Three in development, each extending the same principle: make emerging technology visible, governable, and evidenced.

In development

Three platforms in development, each extending the same visibility-to-evidence discipline into an adjacent domain. Early access participants work directly with the QAISG team.

  1. 01 In Development

    QERA Quantum Ecosystem Reference Architecture

    QERA helps organizations understand the quantum computing ecosystem: providers, capabilities, technology maturity, and commercial readiness, organized into a reference architecture that technology and strategy teams can reason about.

    Portfolio role Extends readiness planning to the quantum ecosystem and post-quantum preparation.

  2. 02 In Development

    QCode AI Software Assurance

    QCode focuses on analysis and assurance of AI-assisted software development and the software risk that comes with it: provenance of generated code, review coverage, dependency exposure, and policy adherence.

    Portfolio role Extends visibility and evidence into AI-assisted software delivery.

  3. 03 In Development

    QScale Startup Financial Intelligence

    QScale brings financial planning and operational intelligence to early-stage companies: runway, hiring plans, unit economics, and operating metrics in one place, designed for founders and operators rather than finance specialists.

    Portfolio role Extends evidence-based operating discipline to the finances of early-stage companies.

    Governance and readiness are not only technical questions. Early-stage companies, including those building on AI and quantum technology, need the same evidence-based clarity in their finances and operations that QAISG brings to enterprise AI. QScale applies that discipline to planning, runway, and reporting.

06 Governance & compliance

Governance that cannot produce evidence is a policy document.

Boards, auditors, and regulators increasingly ask the same question: show us. Enterprises need to connect what they say (policies and frameworks) to what they do (controls and technology usage) and to who did it (identities), with evidence that holds up.

  • Policies
  • Controls
  • Technology usage
  • Identities
  • Evidence
  • Risk
  • Regulatory frameworks

QWatch observes and governs AI activity and records outcomes. QComp keeps the controls, framework mappings, assessments, and reporting. Together they produce an evidence chain from an individual AI interaction to a framework requirement.

07 Emerging technology

Built for the AI enterprises run today, and the technology arriving next.

The same discipline that governs assistants and copilots has to extend to agents, AI-assisted software delivery, and the quantum transition. QAISG's roadmap and advisory practice are organized around that trajectory.

  • Agentic AI

    Agents act on behalf of users and systems. Governance must extend to what agents are permitted to do, which identities they act under, and how their actions are evidenced.

  • Software assurance

    AI-assisted development changes provenance, review, and supply-chain risk. Assurance needs to follow AI into the delivery pipeline.

  • Quantum computing

    A fragmented ecosystem with uneven maturity. Leaders need a structured way to evaluate providers, capabilities, and commercial readiness.

  • Post-quantum readiness

    Cryptographic inventory, migration planning, and vendor alignment are multi-year programs that benefit from starting early and deliberately.

09 Company

Built by operators who have run enterprise technology, security, and governance programs.

QAISG is an early-stage company working with pilot customers. Our credibility rests on the experience behind the platforms and on the discipline with which we build them, not on claims of scale.

  • Enterprise technology operating experience

    The team has led technology, architecture, and transformation programs inside large enterprises, not only advised them.

  • Cybersecurity and risk leadership

    Security operations, identity, and risk management experience informs how QAISG designs visibility and containment.

  • AI governance and compliance practice

    Hands-on work with AI governance frameworks, control design, evidence programs, and regulatory readiness.

  • Product development with pilot customers

    QWatch and QComp are in production and are being deployed with pilot customers whose feedback shapes the roadmap.

Trust Center

Governance technology should be governed well itself.

How QAISG approaches security, privacy, data collection and retention, subprocessors, and responsible AI is documented in the Trust Center.

Get started

Move from AI assumptions to evidence.

Whether you are establishing visibility for the first time or connecting an existing program to frameworks and evidence, start with a conversation about the questions you need to answer.