Prove AI’s impact.
Across your human and agent workforce.
See what AI costs, what your teams produce with it, and which workflows to automate next.
AI ROI
AI spend
$547K
Seats, tokens and cloud models
Hours returned
1,440hrs / wk
36 people-equivalents of capacity
Return on AI spend
2.5×
$1.35M net capacity value
Hours returned per week, by department
Trusted by AI-forward enterprises
AI Value Measurement Platform
Know where your AI investment pays off.
Connect spend and adoption to the work your company delivers. Start with the question you need to answer.
Spend Intelligence
Account for your AI spend.
Trace license and token costs to the teams and agents using them.
ExploreAI Impact
Measure what AI changes.
Compare adoption, fluency and AI capacity across every department.
ExploreDeveloper Intelligence
See what engineering delivers.
Connect Engineering Output, code quality and delivery to AI spend.
ExploreWorkflow Intelligence
Find what to automate next.
Identify repeated work and track automation against a measured baseline.
ExploreToken & Spend Insights
All-in AI spend
$183,847
839 people · 183 agents · 8 models
Where it goes
Spend Intelligence
Know where every AI dollar goes.
Token usage, seat licenses and cloud model costs in one spend view. Trace every dollar to a team, a tool or an agent before the next budget review.
Built for CFOs, finance and operations teams.
Explore Spend IntelligenceAI Impact
Measure AI’s return
across every department.
Connect what each team spends on AI to the hours it returns. Compare adoption, fluency and cost per AI hour to decide where to invest, where to train, and what to scale.
Explore AI ImpactDepartment leaderboard
| Department | AI adoption | Fluency / 10 | Hours returned / wk | Cost per AI hour |
|---|---|---|---|---|
| Engineering | 84% | 6.8 | 520 | $38.00 |
| Customer Support | 71% | 5.6 | 340 | $23.00 |
| Sales | 58% | 4.8 | 240 | $30.00 |
| All 7 departments | 58% | 5.6 | 1,440 | $31.65 |
Developer Intelligence
Measure what engineering delivers with AI.
Connect Engineering Output, code quality and delivery to AI spend. See where coding agents help and where teams need support.
AI Impact · Larridin Router · Agent Effectiveness · Engineering Performance · Ask AI
Explore Developer IntelligenceAI Impact
Engineering Output per $1K of AI spend
67.6pts+31%
AI Quality Score
92/ 100+4
AI ROI
4.8×+0.6
“If you don’t know what people are actually using, you don’t know what to buy next.”
Gainsight used Larridin to understand AI tool adoption and inform its first enterprise LLM purchase.
For your role
Answer the question on your desk.
Heads of AI & CIOs
Where is our AI rollout working?
Compare adoption and capacity across functions. Decide where to expand and where to help.
See AI ImpactCTOs & Engineering Leaders
What are we delivering with AI?
Review Engineering Output, quality and agent performance alongside cost.
See Developer IntelligenceCFOs & Finance Teams
What is our AI spend paying for?
Reconcile costs across vendors. See which teams and agents use the budget.
See Spend IntelligenceFrom the video hub
How leaders put AI to work.
Common questions
Before you get started.
More detail on measurement, data and rollout.
Talk to our teamWhat does Larridin measure?
Larridin is an AI Value Measurement Platform. It connects AI usage and spend to the work of people and agents across your business. Use it to understand adoption and fluency, compare engineering performance, and find opportunities to automate repeated work.
Explore the platform to choose your starting point.
How is AI capacity different from savings?
AI capacity estimates the human-equivalent work AI contributes. It is not automatically time saved, cash returned or a reduction in headcount. The value depends on the baseline, data coverage and how teams use that capacity.
Workflow measurement separates potential opportunities from completed automations. Compare completed work with the captured baseline before reporting realized benefits.
What data needs to be connected?
The sources depend on what you want to measure. Spend Intelligence brings together billing and usage data. Developer Intelligence connects engineering activity, code changes and supported agent sessions. Workflow Intelligence uses captured work activity to identify repeated processes.
Review supported tools, access and coverage with the Larridin team. The Developer Intelligence setup guide explains the engineering setup.
How does Larridin handle privacy and access?
Larridin supports role-based access and enterprise authentication. Choose the scope of measurement and review data handling, retention and permissions with your administrator and security team.
The Trust Center provides security information for your review. Access and collection depend on the products and connections you enable.
How do we start a rollout?
Start with a team and a decision you need to make, such as an AI tool renewal or an engineering rollout. Confirm the relevant data sources, establish coverage and review the baseline before expanding to more departments.
Book a demo to discuss the setup for your environment. The rollout schedule depends on your systems and access requirements.
Where does Developer Intelligence fit?
Developer Intelligence is the engineering part of Larridin. It connects Engineering Output, quality and delivery with AI spend, agent effectiveness and readiness. AI Impact provides the company view across departments.
Explore Developer Intelligence or read the engineering measurement methodology.
Are the dashboard numbers customer results?
No. Dashboards marked “Example” use illustrative data. The company view represents 2,000 employees and 12 weeks of spend. Adoption counts weekly active AI users, and fluency is scored out of 10. All departments are included in the company totals.
AI capacity uses a 40-hour week per people-equivalent. Cost per AI hour divides spend by human-equivalent AI hours over the same period. Workflow examples estimate annual capacity value at $31 per hour over 52 weeks. The opportunity pool includes workflows in pilot and already automated; their figures should not be added together.
The engineering preview uses the separate four-week example on our Developer Intelligence pages. Customer interviews are attributed and linked to their published sources.
You said AI would change your business.
Now prove it’s working.
Walk through Larridin with our team. Bring the question you need to answer.
Book a Demo