We start new companies using thrvAI and our Jobs-to-be-Done method.
We find complex customer jobs in large markets, build agentic intelligence products with thrvAI that get those jobs done faster and more accurately, and fund each new company from seed to product-market fit and Series A. If you are a limited partner, a VC investor, a PE sponsor, or a corporate venture investor contact us to learn more.
thrvAI analyzes hundreds of markets. The ones that meet our criteria become new companies.
- Markets100s analyzed
- thrvAI builds v1Seed funded
- Product-market fitIterated with agents
- Series AFirst round
Customers are not buying a product. They are hiring a product to get a job done.
Clay Christensen
Who we are
We have refined our method since 2013.
Now we use it to
start companies.
A method built with leading companies.
We developed our Jobs-to-be-Done method and platform with Microsoft, Google, American Express, eBay, Oracle, Twitter and Target. The method identifies the unmet needs in the customer’s job and the weaknesses of competitors, based on how fast and accurately their products help the customer get the job done.
A track record of creating equity value.
We have used our method to create equity value with the companies we work with. You can read the case studies and hear directly from the CEOs we have worked with.
Experienced operators and investors.
Jay Haynes, our founder and CEO, was an investment professional at GTCR, a product manager on Windows at Microsoft, and CEO of two startups, one funded by Kleiner Perkins and the other by DFJ. Jay leads the thrv team of executives from leading technology companies, supported by experienced advisors. Learn more about us.
- v1SaaS era
2013 - v2SaaS era
2015 - v3SaaS era
2020 - thrvAIAgentic Platform
2023 - thrv PortfolioStarting new companies
2026
“The application layer on top, ultimately, is where economic benefit will happen.”
Jensen Huang
Our method
Technology changes.
The customer’s job does not.
This is a competitive advantage for our portfolio companies.
Theodore Levitt of Harvard Business School famously said, “Customers don’t want a quarter-inch drill, they want a quarter-inch hole.” This is true in every market. Products change with each wave of technology, from the CPU in the 1970s to the internet in the 1990s to AI in the 2020s, but the customer’s job stays the same. This is why the customer’s job is the North Star and competitive advantage for our portfolio companies.
Consumer
Consumers don’t want iPods.
They want to create a mood with music.
- Vinyl 1964
- Optical 1984
- Hard drive 2001
- Cellular 2007
- Streaming 2021
Business
Salespeople don’t want CRM.
They want to acquire new customers.
- Phone 1876
- Email 1972
- On-premise 1993
- SaaS 2002
Health
Surgeons don’t want stents.
They want to restore artery blood flow.
- Amputation 1800
- Balloon 1964
- Stent 1986
- Drug-eluting stent 2002
The customer’s job
Every job has traffic jams.
Our portfolio companies find the alternative routes.
Customer jobs are complex. A typical job has 15 to 20 steps to plan, execute, assess, revise and conclude the job. Each step has 10 to 15 customer needs, for 120 to 150 needs in total, and every job has metrics, root causes, constraints and emotions.
Take the job of getting to a destination on time. Like every job, it has the equivalent of traffic jams that keep the customer from getting the job done. The customer has to make an important and difficult decision about whether to take an alternate route to arrive on time.
With thrvAI, our portfolio companies build the equivalent of full self-driving agents: intelligent agents that get the job done for the customer as automatically as possible to create economic value for the customer.
- 20Job steps
- 140Needs
- 25Metrics
- 35Root causes
- 40Constraints
Get to a destination on time
- Determine the routePlan
- Travel to the destinationExecute
- Assess if the arrival time is accurateAssess
- Revise the route if neededRevise
- Arrive at the destinationConclude
From job to strategy
The job is the market.
thrvAI finds the strategy for our portfolio companies.
We define each market for each of our portfolio companies by the customer’s job, not by the products. Customers want holes, not drills. The customer’s job is the market.
We pioneered and patented sizing market opportunities by the customer’s willingness to pay to get the job done rather than by the price of current products. This is how we size the markets for our portfolio companies. This same analysis is how we identify the target customer segment and the ideal customer profile for our portfolio companies.
thrvAI identifies the unmet needs in each step of the job and where competitors’ products fall short in getting the job done fast and accurately.
thrvAI uses this analysis to set the optimal strategy for an agentic intelligence product that gets the job done and creates economic value for customers.
Investment criteria
What we look for when we start a new portfolio company.
With thrvAI, we are analyzing hundreds of business, consumer and health markets against five investment criteria.
Our first criterion is a large market with a complex customer job, where customers struggle to get the job done quickly and accurately with the competitive products in the market today.
We look for jobs where it is difficult for customers to make the important decisions that determine whether they succeed.
We look for jobs where intelligence and compute can get the job done faster and more accurately.
We target large markets, sized by the customer’s willingness to pay to get the job done, the frequency of the job execution, the number of customers in the market, the economic value of the job, and the opportunity to disrupt the incumbents.
We look for jobs where getting the job done better has a meaningful impact on people’s lives. This is the criterion we weigh most.
The process
How we start a new portfolio company.
Step 01
We identify markets that meet our criteria
thrvAI maps the customer’s job-to-be-done, finds the unmet needs and competitor weaknesses, and sizes the market by willingness to pay. We are running this analysis on hundreds of markets.
Step 02
We start the company and build v1
When a market meets our criteria, we start the company, provide the seed funding, and build v1 of the new agentic intelligence product with thrvAI.
Step 03
We iterate to product-market fit
We put the product in the hands of customers and iterate rapidly with thrvAI agents until the company reaches product-market fit.
Step 04
We raise Series A capital to grow
Once our portfolio company has product-market fit, we raise Series A capital to grow the company with thrvAI.
What we build for each company
Full self-driving agents for the customer’s job
The harness drives the whole job to completion. It maintains the state of the entire job, ingests updates, runs agents concurrently, and determines the next action. thrvAI creates the intelligence that guides the agents to refine their work and adjust the plan as they learn, carrying the job from request to result without the customer managing every step.
thrvAI maps the customer’s job and builds specialized agents to Plan, Execute, Assess, Revise and Conclude the job. Each agent owns a distinct part of the job, with the context, tools and expertise to get it done on the customer’s behalf.
thrvAI runs evals autonomously, continuously improving the economic value created for customers as measured by the metrics in the job.
When a run fails, thrvAI reads the trace, labels the failure, finds the first span where it went wrong, and fixes the error.
Each product gets an MCP tool surface, so its job agents can read and act on any of the customer’s systems of record.
Proprietary open-weight models are trained for each job step on the company’s own job executions and expert preferences.
Customers pay for the outcome of getting the job done, and the cost of each job execution is managed as a gross margin line.
Market opportunity
thrvAI uses the customers’ JTBD to identify the market opportunity for agentic growth.
Traditional market definitions are based on products, and the size of the market is based on the price of the product and the number of customers. To succeed at disruption, we define the market based on the customer’s job-to-be-done and their willingness to pay to get their job done. Then our thrvAI agents identify the steps, needs, metrics, root causes, and constraints in the customer’s JTBD. Our thrvAI agents analyze the competitors’ weaknesses and create the optimal agentic product strategy in the target market.
JTBD Harness
thrvAI builds a JTBD agent harness that drives the job successfully.
thrvAI creates a JTBD Agent Harness that drives the whole job to completion for the customers. The harness maintains the state of the entire job, ingests updates, runs agents concurrently, and determines the next action to get the job done. It's intelligence guides the agents to refine their work and adjust the plan as they learn, carrying the job from request to result without the customer having to manage every step.
Legacy business
Roadmap commitments and sprint planning decide what ships next.
Agentic business
thrvAI uses the customer’s job to decide what each agent does, in parallel.
Job Step Agents
thrvAI builds an autonomous agent team for the customer’s job.
thrvAI maps the customer’s job-to-be-done and builds specialized agents to Plan, Execute, Assess, Revise, and Conclude the job for the customer. Each agent owns a distinct part of the job, with the context, tools, and expertise to get the job done on the customer’s behalf.
Legacy business
Feature specs and acceptance criteria describe how screens should behave.
Agentic business
thrvAI creates job step agents that create economic value for the customer.
Evals
thrvAI creates evals that improve accuracy every day.
thrvAI runs evals autonomously in the background. Domain experts label the cases that define a job done correctly, including the edge cases only experienced practitioners recognize, and thrvAI generates new cases from every job execution. It runs the suite on every change, scores accuracy, and ships the improvements that raise it.
The team sets the standard for a job done correctly. thrvAI does the work of meeting it, around the clock, as it builds the agentic intelligence product that gets the customer’s job done for them.
Legacy business
QA tests features against expected behavior before a release train leaves.
Agentic business
thrvAI runs evals autonomously on every change, and improvements ship daily.
Error analysis
thrvAI conducts error analysis on every failed run.
thrvAI conducts error analysis autonomously in the background. When a run fails, thrvAI reads the trace, labels the failure, finds the first span where it went wrong, and updates the failure taxonomy. It then fixes the cause in the harness, the evals, or the model, re-runs the evals, and ships the fix when accuracy improves.
The team reviews what changed. The product that gets the customer’s job done keeps improving without waiting for a release.
Legacy business
Support tickets arrive after the customer has already been let down.
Agentic business
thrvAI finds, labels, and fixes failed runs before they become tickets.
MCP tool surface
thrvAI generates an MCP tool surface that works on any system of record.
thrvAI exposes the new product’s capabilities through an MCP tool surface, so the agents can read and act on other vendors’ systems of record. Customers can put the agents to work without replacing the software they already run.
The market grows to every customer who has the job, including customers running a competitor’s system.
Legacy business
The product creates value only inside its own database.
Agentic business
thrvAI agents get the job done using the customer’s data wherever it lives.
Proprietary models
thrvAI trains custom models on the customers’ job executions.
Every job execution and every expert correction is training data. thrvAI trains open-weight models for each job step. Each step gets a model that is more accurate for that step and less expensive to run than a general-purpose model.
The more jobs the new product executes, the more accurate and less expensive each model becomes.
Legacy business
Story points and feature delivery measure progress.
Agentic business
thrvAI creates open-weight models based on the job execution to create economic value for the customer at lower cost.
Pricing and margin
thrvAI creates a new agentic product priced on the economic value created for the customer.
Agents are priced against the economic value of the job, not the number of seats. thrvAI supports outcome or consumption pricing and tracks the cost of each job execution (inference, tool calls, and expert escalation) as a gross margin line.
Customers pay for jobs done. You manage the margin on each one.
Legacy business
Seat-based pricing and renewal management.
Agentic business
thrvAI creates a new agentic product priced on the economic value created for customers with cost per job execution managed as gross margin.
Why we do it
Intelligent agents will get the job done for customers to create economic value and improve their lives.
This is the reason behind each of our investment criteria. The most important is human impact: helping customers get their jobs done better so they can live better lives.
Learn more about the thrv Portfolio.
If you are an investor, an executive, or an expert in a complex customer job, get in touch. We would like to meet you.