| Dimension | Worklytics | Larridin | Why It Matters |
|---|---|---|---|
| Core platform | Workplace collaboration analytics | AI Execution Intelligence | Shapes what gets built deeply vs. added on |
| AI tools covered | ~9 major AI platforms | 3,000+ AI tools including internal/homegrown — growing daily | Enterprises use 200–300 AI tools. 9 is a fraction. |
| Adoption model | Usage tracking + correlation to productivity outcomes | Four-layer framework: Usage, Depth, Breadth, Segmentation | Single-layer vs. multi-dimensional measurement |
| Engagement depth | Activity-level metrics (usage frequency, session counts) | Adoption spectrum: non-user → explorer → regular → power user → AI-native | Distinguishes "logged in" from "changed how they work" |
| Modality tracking | Not explicitly segmented | Text, code, image, audio, video — tracked per user and department | Reveals whether AI is embedded across work types or stuck on chat |
| Agentic AI measurement | Not covered | Agentic vs. interactive ratio, agentic consumption & spend velocity | Critical for 2026 as autonomous AI agents scale |
| Shadow AI detection | Not a focus area | Continuous detection across 3,000+ tools — sanctioned, tolerated, and unsanctioned | You can't govern what you can't see. 83% of enterprises report Shadow AI growing faster than IT can track. |
| Proficiency measurement | Power user identification | 9-dimension proficiency model with progression tracking | Adoption without proficiency is activity without value |
| Internal/homegrown AI tools | Not supported | Supported — internal AI tools tracked alongside commercial tools | Many enterprises build custom AI systems. If you can't measure them, your adoption picture is incomplete. |
| Privacy approach | Pseudonymization proxy deployed on customer infrastructure; no content monitoring | Privacy-first, aggregate-level reporting; no content monitoring | Both strong. Both GDPR/CCPA compliant. |
Larridin's advantage is focus. The entire platform is built for one thing: measuring how enterprises adopt, use, and create value from AI. That focus produces depth that a broader platform can't match:
This is the foundational difference. Worklytics integrates with approximately 9 AI tools — the major platforms like Microsoft Copilot, ChatGPT Enterprise, Google Gemini, Claude, and GitHub Copilot. For organizations whose AI usage is concentrated in these tools, that may be sufficient.
But most enterprises don't use just 9 AI tools. Audits consistently reveal 200–300 AI tools in active use when leadership estimated 60–70. Larridin's library of 3,000+ tools — growing daily — covers the full spectrum: major platforms, niche vertical tools, open-source models, and critically, internal and homegrown AI systems that enterprises build themselves.
If you can only see 9 out of 200+ tools, your adoption data is a sample, not a census. Every metric derived from that sample — adoption rate, engagement depth, power user density — is understated, and the gap between your dashboard and reality grows as employees adopt more tools.
Worklytics tracks AI usage: who's using which tools, how often, with what frequency. This is Layer 1 of Larridin's four-layer framework.
Larridin adds three layers:
The difference matters because usage alone can't distinguish between an employee who asked ChatGPT one question and an employee who runs multi-tool AI workflows across three modalities daily. Both are "active users." Only one is experiencing productivity gains.
As of 2026, 80% of Fortune 500 companies use active AI agents (Microsoft, 2026). Agentic AI — where AI plans, executes, and delivers results autonomously — is a fundamentally different usage pattern from interactive prompting.
Larridin tracks:
Worklytics does not currently provide agentic measurement. For organizations deploying AI agents at scale, this is a visibility gap that grows with every new agent workflow.
Larridin's 3,000+ tool library enables continuous Shadow AI detection — identifying unsanctioned AI tools in use across the organization and classifying them by risk tier. 83% of enterprises report Shadow AI growing faster than IT can track (Larridin, 2025).
Worklytics' architecture — connecting to ~9 specific AI tools — means that any AI usage outside those 9 tools is invisible. It can't detect what it isn't connected to. Shadow AI detection requires knowing what exists beyond your sanctioned toolset, which requires a tool library that extends far beyond the major vendors.
Larridin is the right choice when:
Worklytics is the right choice when:
| Question | Worklytics | Larridin |
|---|---|---|
| "What % of employees used AI this week?" | Yes — for ~9 integrated tools | Yes — across 3,000+ tools including internal systems |
| "Are they using AI deeply or just dabbling?" | Limited — frequency and session counts | Yes — adoption spectrum, engagement depth scoring |
| "Which departments are leading and lagging?" | Yes — segmented by team | Yes — segmented by department, role, geography, hierarchy, tenure |
| "Are employees using AI for text only, or across modalities?" | No | Yes — text, code, image, audio, video tracked per user |
| "How much work are AI agents doing autonomously?" | No | Yes — agentic ratio and consumption tracking |
| "What unsanctioned AI tools are employees using?" | No — only sees connected tools | Yes — Shadow AI detection across 3,000+ tool library |
| "Are people getting better at using AI, or just using it more?" | Limited — identifies power users | Yes — 9-dimension proficiency model with progression tracking |
| "How do our meeting patterns and collaboration look?" | Yes — deep meeting analytics, manager effectiveness | No — not a workplace analytics platform |
| "What are our employees' work-life balance patterns?" | Yes — overtime, after-hours, weekend work | No — focused on AI adoption |
Worklytics is a workplace collaboration analytics platform that includes AI adoption tracking as one use case. Larridin is purpose-built for AI Execution Intelligence — adoption, proficiency, and impact measurement is the entire product. The difference shows up in depth: Larridin covers 3,000+ AI tools (vs. ~9), measures adoption across four layers (vs. usage tracking), tracks agentic AI and modality mix, and detects Shadow AI.
Yes — Worklytics tracks AI tool usage for approximately 9 major platforms including Microsoft Copilot, ChatGPT Enterprise, Google Gemini, Claude, and GitHub Copilot. It provides usage frequency, team-level segmentation, and correlation to productivity outcomes. For organizations whose AI usage is concentrated in these major platforms, this may provide sufficient visibility.
Larridin's library covers 3,000+ AI tools — including major platforms, niche vertical tools, open-source models, and internal/homegrown AI systems — with the library growing daily. This matters because enterprises typically use 200–300 AI tools when audited, far exceeding what leadership estimates. Full ecosystem visibility requires coverage that extends beyond the top vendors.
No — Worklytics connects to specific AI tools via API integrations and reports on usage within those connected tools. AI usage happening outside those ~9 integrations is not visible. Shadow AI detection requires a tool library that extends far beyond the major vendors, which is where Larridin's 3,000+ tool coverage provides an advantage.
No — Larridin is focused exclusively on AI adoption, proficiency, and impact measurement. It does not provide meeting analytics, collaboration pattern analysis, or work-life balance metrics. Organizations that need both AI adoption depth and broad workplace analytics may use both platforms.
Yes — the platforms are complementary, not competing. Worklytics provides broad workplace analytics (collaboration, meetings, manager effectiveness). Larridin provides deep AI adoption measurement. Organizations that need both capabilities can run them in parallel. If you need to choose one, the decision depends on whether your primary need is workplace analytics broadly or AI adoption measurement specifically.
^1 Microsoft Security Blog, "80% of Fortune 500 Use Active AI Agents," February 2026.
^2 Larridin, "State of Enterprise AI 2025," n=567 companies across 12 industries. Updated every 2–3 weeks.
^3 McKinsey Global Survey on AI, 2026.
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