Larridin
by Larridin, Inc.
AI value measurement platform that tracks enterprise AI spend, adoption and output across human and agent work
Larridin is an AI value measurement platform for enterprises that want to know what their AI tools cost, who actually uses them, and whether team output changes as a result. It is built for CIOs, finance leaders and engineering heads who are renewing AI licences and token budgets without usage or ROI data to justify them.
Larridin is an enterprise AI measurement platform from Larridin, Inc., a South San Francisco company founded in 2024 by Russ Fradin (CEO) and Jim Larrison (President), who both worked on digital measurement at Comscore, with Ameya Kanitkar (CTO, formerly of LinkedIn, Coinbase and Groupon). The product is organised into modules. Spend Intelligence reconciles licence, token, seat and cloud model costs across vendors and traces them to teams, tools and agents. AI Impact compares adoption, fluency and returned capacity by department, including a cost per AI hour. Developer Intelligence connects engineering output, code quality and delivery metrics such as PR cycle time, change failure rate and defect rate to AI spend, and captures coding-agent sessions from Claude Code, Codex, Cursor and Copilot with token usage and estimated cost. Workflow Intelligence finds repeated work and tracks automation against a measured baseline. An Ask AI connector for MCP clients is in beta, and a prompt router that sends work to frontier or cheaper open-weights models was announced as a planned product. On November 2, 2026 Larridin announced a $30 million Series A led by Pelion Ventures, bringing total funding to $47 million, and said it had measured more than 2 billion AI sessions and 82,000 workflows. Named customers include SurveyMonkey, Vertiv, Klaviyo, Gainsight, Globality, TigerConnect, EcoVadis and Sundt. It competes with engineering-intelligence vendors such as DX, Jellyfish, Faros AI, LinearB and Swarmia, but covers spend and non-engineering functions as well.
A CIO or CFO-aligned AI program office that owns several AI licences and token budgets and has to report adoption and ROI to the board
One view of AI spend by team, tool and agent, tied to usage and output metrics, so renewals and cuts are decided on measured data
At a Glance
- Category
- Governance & Security
- Pricing
- Contact for pricing
- Target Market
- CIOs, CTOs, CFOs, Engineering Leaders, AI Program Offices
- Deployment
- Cloud-only
- Founded
- 2024
- Headquarters
- South San Francisco, United States
Key Features
- ✓Spend Intelligence
Reconciles licence, token, seat and cloud model costs across AI vendors and attributes them to teams, tools and agents.
- ✓AI Impact
Compares adoption, fluency and returned capacity by department, including a cost per AI hour metric for each group.
- ✓Developer Intelligence
Links coding-agent sessions, token usage and estimated cost to PR cycle time, change failure rate and defect rate on merged work.
- ✓Agent Effectiveness and Readiness
Scores Claude Code, Codex and Cursor sessions and checks repositories for skills, MCP setup and guardrails before wider agent rollout.
- ✓Workflow Intelligence
Identifies repeated work across functions and tracks automation progress against a measured baseline in an AI Transformation Center.
- ✓Ask AI MCP connector (beta)
Lets Claude, Cursor, VS Code and other remote MCP clients query Larridin measurement data in natural language.
Use Cases
- •AI licence renewal decisions
An IT team sees which purchased AI seats go unused and which tools teams actually adopt, then renews or cuts with usage evidence.
- •Coding-agent ROI
Engineering leaders compare cost per shipped change across AI coding tools; Larridin reported a 66x gap between two comparable tools at one customer.
- •Token spend concentration
Finance spots that a small number of users drive most token cost, as at one customer where one engineer accounted for about 65% of weekly spend.
- •First enterprise LLM purchase
Gainsight used Larridin to learn which AI tools employees already used before choosing its first enterprise LLM contract.
Ideal For
Best For
- ✓Reconciling seat, token and API costs from several AI vendors into one spend view by team
- ✓Measuring how much engineering output changes as coding agents such as Claude Code, Cursor and Copilot are rolled out
- ✓Finding shadow AI use and low-adoption licences before a renewal
- ✓Building a measured baseline before automating repeated workflows outside engineering
Not Ideal For
- ✗Small teams with one or two AI tools, where vendor admin consoles already show usage and published pricing is unavailable to compare cost
- ✗Engineering orgs that only want deep code-level productivity analytics, since Larridin's own docs describe its data sources generically and name no GitHub or Jira connector
- ✗Buyers who need peer reviews before shortlisting, because no G2 or Capterra review base exists yet
Deployment
Market Analysis
Pros
- ✓Covers spend, adoption and output in one product, which is what boards ask AI programs to report
- ✓Tracks the coding agents most enterprises are rolling out, including Claude Code, Codex, Cursor and Copilot
- ✓Named mid-market and enterprise customers such as SurveyMonkey, Klaviyo, Vertiv and Gainsight
- ✓Shows SOC 2 Type II, GDPR and HIPAA badges and supports SSO and SCIM
Cons
- ✗No published pricing and no self-serve trial; every path goes through sales
- ✗No reviews on G2 or Capterra yet, so outcome claims such as a 47% output increase come only from the vendor
- ✗Docs describe data sources generically and do not list named connectors such as GitHub or Jira
- ✗The prompt router announced with the Series A is planned, not shipped
Pricing
Enterprise
Contact for pricing
- ✓Spend Intelligence
- ✓AI Impact
- ✓Developer Intelligence
- ✓Workflow Intelligence
- ✓SSO and SCIM
Larridin publishes no list prices; the Get Pricing, Try Now and Book a Demo buttons all lead to a sales contact form. Pricing is quoted per organisation after a demo, and there is no self-serve tier to test before talking to sales.
Security & Compliance
Connect
Sources
This page was written from 6 sources, 3 on domains other than larridin.com.
- 1.larridin.com — larridin.comvendor
- 2.larridin.com — larridin raises 30 million series a to prove the impact of avendor
- 3.ai-spend.larridin.com — developer productivity
- 4.larridin.com — ai agent productivity platforms 2026vendor
- 5.finance.yahoo.com — larridin raises 30 million series 170000208
- 6.gii.tw — fs2053314 measuring real work ai
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