Support
Rollout is guided through a demo with the Larridin team. A Developer Intelligence setup guide, methodology page and a Trust Center for security information are available.
Learn moreLarridin
Measure AI spend, adoption and output across people and agents
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What is Larridin?
Larridin is an enterprise AI value measurement platform that connects AI spend, adoption and fluency to the work people and agents produce, with modules for spend, department impact, engineering output and workflow automation.
Larridin is an AI value measurement platform aimed at enterprises that have bought AI tools and now need evidence of what they deliver. It links usage and spend to the work done by employees and software agents, so leadership can see what AI costs, who uses it, and what comes out the other end. The product is organised around four starting points. Spend Intelligence combines seat licenses, token usage and cloud model costs into one view and traces them to teams, tools and agents, which suits finance and operations groups preparing a budget review. AI Impact compares adoption, fluency (scored out of 10) and hours returned across departments, with a cost per AI hour figure to guide where to invest, train or scale. Developer Intelligence ties engineering output, code quality and delivery to AI spend and looks at coding agent effectiveness. Workflow Intelligence studies observed activity to find repeated work, then tracks candidate automations from identified to pilot to live against a captured baseline. In practice, a rollout starts with one team and one decision, such as an AI tool renewal or an engineering rollout. The relevant data sources are connected, coverage is confirmed and the baseline is reviewed before more departments are added. Which sources are needed depends on the module: billing and usage data for spend, engineering activity and supported agent sessions for developer metrics, and captured work activity for workflow discovery. Role-based access and enterprise authentication are supported, and a trust center covers security details. The homepage is careful to say that AI capacity is an estimate of human-equivalent work, not automatically time saved or reduced headcount, and that its dashboards are illustrative examples rather than customer results. Larridin sits among AI governance, FinOps and developer analytics tools, but covers all three angles in a single measurement layer. It is built for CIOs, heads of AI, CTOs and CFOs rather than individual users, and it is sold through a demo conversation.
How do you use Larridin?
1Pick a starting question
Choose one decision to anchor the rollout, such as an AI tool renewal, an engineering rollout or a budget review. Then pick the matching module: spend, impact, developer or workflow.2Book a demo
Request a walkthrough with the Larridin team and bring the question you need to answer. Setup and rollout schedule are discussed against your own systems and access needs.
3Connect the data sources
Confirm which billing, usage, engineering or work activity sources apply to your chosen module. For engineering teams, the setup guide explains the connection steps.
4Review coverage and baseline
Check data coverage and establish the baseline for one team before drawing conclusions. Reviewing the engineering methodology helps interpret the output metrics.
5Review security and access
Work with your administrator and security team to set measurement scope, retention and permissions. The trust center holds the security documentation.
6Expand to more departments
Once the first team's numbers are trusted, widen measurement to other departments and compare adoption, fluency and cost per AI hour.
Pros and cons
Pros
- Covers spend, adoption, engineering output and workflow automation in one measurement layerAI
- Traces license and token costs to specific teams, tools and agentsAI
- Tracks both human and agent usage rather than only seat-based adoptionAI
- Candid about limits: AI capacity is described as an estimate, not guaranteed savingsAI
- Role-based access, enterprise authentication and a public trust center for security reviewAI
Cons
- Sales-led: the only entry point shown is booking a demo, with no self-serve signupAI
- No pricing is published on the homepage, so budgeting requires a conversationAI
- Dashboards shown are illustrative examples, not verified customer outcomesAI
- Value depends on baseline quality, data coverage and which integrations are supportedAI
- Aimed at large organisations and likely excessive for small teams or individualsAI
How much does Larridin cost?
Integrations
Connects billing and usage data, engineering activity, code changes, supported agent sessions and captured work activity. Supported tools and coverage are confirmed with the Larridin team.
Learn moreFeatures
Spend Intelligence for license, token and cloud model costs; AI Impact for adoption, fluency and cost per AI hour by department; Developer Intelligence for engineering output, quality and agent effectiveness; Workflow Intelligence for finding and tracking automation candidates.
Frequently asked questions about Larridin
How do you use Larridin?
The walkthrough on this page covers 6 steps: 1. Pick a starting question 2. Book a demo 3. Connect the data sources 4. Review coverage and baseline 5. Review security and access 6. Expand to more departments.What platforms does Larridin support?
Larridin is available on Web App.What does Larridin integrate with?
Connects billing and usage data, engineering activity, code changes, supported agent sessions and captured work activity. Supported tools and coverage are confirmed with the Larridin team.What are the limitations of Larridin?
Sales-led: the only entry point shown is booking a demo, with no self-serve signup. No pricing is published on the homepage, so budgeting requires a conversation. Dashboards shown are illustrative examples, not verified customer outcomes.
Status
StatusActive
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Added10/8/2026
Platforms
Web App
Pricing
Paid
