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thrv

Build the agentic product that gets your customer’s job done.

thrvAI is our platform for building agentic intelligence products that do the customer’s job for them, faster and more accurately than legacy software. The result is a new business that creates economic value your customers can measure and equity value for your company.

Contact us How it works

Your customer’s job

agent run

thrvAI builds agents that get your customer’s job done for them, step by step.

  1. Plan Done
  2. Execute 3 in parallel
  3. Assess Running
  4. Revise Queued
  5. Conclude Queued

orchestrator · 3 concurrent runs · 1 reroute

Disruption

Agents are a disruptive technology for software.

Clay Christensen showed that incumbents improve their products along a sustaining trajectory for their most demanding customers, and eventually overshoot what most customers can use. A disruptive technology enters below mainstream needs, improves faster, and takes the market with a different business model.

Legacy software is on the sustaining trajectory. It keeps adding features that organize the inputs to the customer’s job, while the customer still does the work. Agentic intelligence products do the job for the customer, and they improve every day against evals.

How agentic intelligence products disrupt legacy software

Adapted from Clay Christensen’s model of disruptive innovation

Agentic intelligence products Legacy software Performance customers can use
Most demanding customers Mainstream customers Job performance customers can use Legacy software Sustaining innovation Overshoot More features, same manual work Agentic intelligence products Disruptive innovation Enters below mainstream needs Agents get the job done well enough for mainstream customers, priced on results Agents pass legacy software Job performance: speed and accuracy Time Customer needs Legacy software Agentic intelligence products Good enough for mainstream customers Agents pass legacy software Time Job performance

Legacy software organizes the inputs

Records, workflows, and dashboards help the customer manage the job. The customer still executes it.

Agents get the job done

An agentic product executes the job steps and is measured by how fast and accurately the job gets done.

The business model changes

Agents are priced against economic value for customers. Seat counts stop being the unit of value.

Christensen found that incumbents survive disruption by building the new business in an autonomous team. thrvAI is the platform those teams use.

How thrv disruption teams work

Market opportunity

thrvAI uses your customers’ JTBD to identify your 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 redefine your market based on your 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 your customer’s JTBD. Our thrvAI agents analyze your competitors’ weaknesses and create the optimal agentic product strategy in your market.

Product market price × number of customers today's revenue pool redefine Job market willingness to pay to get the job done agentic growth opportunity thrvAI agents analyze your customer's JTBD Plan Execute Assess Revise Conclude Steps Needs Metrics Root causes Constraints Unmet needs in the job where the job is slow or inaccurate Competitors' weaknesses where their products fail the job Optimal agentic product strategy for your market

An agentic business

How thrvAI builds disruptive agentic intelligence products

An agentic product is a different business from the legacy product that funds it. It is built, measured, and priced differently. thrvAI provides the system for each part of it, starting with the customer’s job-to-be-done.

Your legacy business today

  • Roadmap commitments and sprint planning
  • Feature specs and acceptance criteria
  • QA against expected behavior
  • Support tickets as the feedback loop
  • A product that works inside its own database
  • Story points and feature delivery
  • Seat-based pricing and renewal management

An agentic business with thrvAI

  1. 01Agents for each job step, run concurrently and rerouted by an orchestrator
  2. 02A harness per job step with enforced output contracts
  3. 03Evals that thrv AI runs autonomously in the background
  4. 04Autonomous error analysis on every failed run
  5. 05An MCP tool surface that works on any system of record
  6. 06Proprietary open-weight models trained per job step
  7. 07Outcome or consumption pricing managed to gross margin
01

Job step agents

thrvAI builds an agent for every step of your customer’s job.

thrvAI maps your customer’s job-to-be-done and builds an agent for each job step category: Plan, Execute, Assess, Revise, and Conclude. An orchestrator holds the job state, so each agent knows what has been done, what comes next, and what the customer needs at the end.

The orchestrator runs independent job steps concurrently and reroutes work when a step’s output needs another pass, so the job gets done faster than a fixed sequence allows. Each agent is accountable for its step, and the orchestrator is accountable for the whole job.

Legacy business

Roadmap commitments and sprint planning decide what ships next.

Agentic business

The customer’s job decides what each agent does, in parallel where it can.

Orchestrator job_state { parallel: 3, reroutes: 1, status } CONCURRENT Plan Done Execute run 1 · running Execute run 2 · running Execute run 3 · retry Assess running reroute: needs another pass Revise Conclude The customer's job, executed end to end Concurrent where steps are independent, rerouted when a step needs another pass
02

Harnesses

thrvAI creates a harness around every customer job step.

Each agent runs inside a harness that assembles the context it needs, grants access to the right tools, and enforces an output contract. When an output fails the contract, the harness reroutes the work, retries with new context, or escalates to a domain expert.

Contracts make agent behavior predictable enough for customers who depend on the result.

Legacy business

Feature specs and acceptance criteria describe how screens should behave.

Agentic business

Output contracts define what a finished job step must contain.

Context assembly job state, records, prior steps Tool access scoped to this job step Job step agent step: Assess Output contract schema · fields · confidence Pass Hand off to the next job step Fail Reroute, retry, or escalate
03

Evals

thrvAI creates evals that improve accuracy every day.

thrvAI runs your evals autonomously in the background. Your disruption team’s 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.

Your 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 your 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.

thrvAI eval loop · autonomous running in the background Generate cases Run the suite Score accuracy Ship repeats on every change, around the clock Eval suite · Assess step source Routine case expert Pass Conflicting sources thrvAI Fixed Expert edge case expert Running Accuracy against the eval suite Illustrative First release Daily releases, shipped by thrvAI
04

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.

Your team reviews what changed. The product that gets your 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.

thrvAI error analysis · autonomous running in the background Trace · Execute step run 8841 · failed execute_step assemble_context tool: search_records llm: draft_output first failing span Read trace every failed run Label the failure Fix the root cause Re-run evals confirm the fix Ship no release train Failure taxonomy maintained by thrvAI Missing context Wrong tool selected Contract violation Reasoning error Missed escalation
05

MCP tool surface

thrvAI generates a tool surface that works on any system of record.

thrvAI exposes your product’s capabilities through an MCP tool surface, so your agents can read and act on other vendors’ systems of record as well as yours. Customers can put your agents to work without replacing the software they already run.

Your 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

The agents get the job done wherever the customer’s data lives.

Your system of record Yours ERP Another vendor CRM Another vendor HRIS Another vendor Document management Another vendor Email and calendar Another vendor MCP tool surface Your agentic product Job step agents read act
06

Proprietary models

thrvAI trains custom models on your customers’ job executions.

Every job execution and every expert correction is training data. thrvAI trains open-weight models for each job step on your executions and your experts’ preferences. 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 your product executes, the more accurate and less expensive each model becomes.

Legacy business

Story points and feature delivery measure progress.

Agentic business

Accuracy and cost per job step measure progress, and the models improve both.

Job executions every run, traced Expert preferences corrections and rankings Training per job step open weights Plan model Execute model Assess model Revise model Conclude model Deployed models execute more jobs, which produce more training data Higher accuracy per step Lower cost per execution
07

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

Outcome or consumption pricing, with cost per job execution managed as gross margin.

What the customer compares Economic value Agentic product price Customer's economic gain Unit economics per job execution Price per job execution Gross margin Model inference Tool calls Expert escalation Gross margin Every model the team trains and every failure it fixes lowers cost per execution and widens the margin.

Tell us your customer. We’ll show you your agentic market opportunity.

Schedule a working session with our JTBD and AI experts. We will walk you through your customer’s unmet needs and your competitors’ weaknesses, and show you a new agentic product and strategy to beat your competition, all using thrvAI, live.

Contact us