Scaling AI Agents to Replace SaaS and Disrupt Healthcare
Curative CEO Fred Turner details how custom AI agents replaced 80% of legacy SaaS spend, scaled provider contracting by 10x, and pivoted a $5B pandemic testing business into a $1.3B health insurer. Learn how orthogonal supply chains and AI-driven workflows are reshaping enterprise operations.
Curative’s journey from pandemic testing to a $1.3 billion health insurer reveals a fundamental shift in enterprise operations: the rapid displacement of legacy SaaS by custom AI agents. By developing internal tools for CRM, claims processing, and data visualization, the company eliminated 80% of its software spend. This move underscores a critical lesson for modern enterprises: off-the-shelf software often creates administrative drag, whereas bespoke AI solutions integrate seamlessly with proprietary workflows, reducing costs and accelerating execution.
Scaling Through Orthogonal Supply Chains
During the COVID-19 surge, Curative scaled to 206,000 daily tests by rejecting traditional lab efficiency models. Instead, they engineered an "orthogonal supply chain," sourcing non-standard materials and alternative vendors to bypass industry bottlenecks. This approach demonstrates that crisis scaling requires abandoning incremental optimization in favor of radical process redesign. Companies facing exponential demand must prioritize capacity expansion over marginal efficiency gains, even if it means temporarily accepting higher per-unit costs.
AI as a Volume Multiplier
The deployment of AI agents like "Gwen" for provider contracting illustrates how automation can transform business models. Rather than merely replacing human workers, Curative used AI to increase contracting volume from 100 per week to 100 per day. This shift reveals a fundamental strategic advantage: AI’s true value lies in its ability to unlock previously impossible scale. Organizations that leverage AI purely for headcount reduction miss the opportunity to expand market reach and revenue potential.
The Future of Healthcare Market Structure
Fred Turner argues that US healthcare inefficiency stems from extreme consolidation among payers and providers. Monopolistic structures force negotiated pricing that inflates costs without improving outcomes. Breaking these entities into smaller, competitive units would restore market dynamics, driving down prices and fostering innovation. This structural critique offers a roadmap for policymakers and entrepreneurs seeking to disrupt stagnant industries.
Preparing for the Agent Economy
As AI assumes routine back-office functions, new operational roles will emerge. "Agent supervisors" will become essential for managing exceptions, approving strategic deviations, and maintaining quality control. Meanwhile, human capital will shift toward technical oversight, complex relationship management, and high-stakes decision-making. Organizations that proactively restructure their teams around AI-augmented workflows will gain a decisive competitive edge, transforming cost centers into scalable growth engines.
Key insights
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Custom AI agents can replace expensive SaaS subscriptions by integrating directly into proprietary workflows, eliminating administrative overhead and reducing software spend by up to 80%.
Impact: Companies can drastically lower fixed costs while improving process agility and data security.
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AI-driven contracting agents increase throughput exponentially by handling repetitive outreach and negotiation, freeing human teams to focus on high-value relationship building.
Sales & Business Development →
Impact: Organizations can scale provider networks or sales pipelines without proportional headcount increases.
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Crisis scaling requires abandoning efficiency-optimized legacy processes in favor of orthogonal supply chains that bypass traditional bottlenecks.
Impact: Businesses can rapidly expand capacity during market shocks by prioritizing volume over marginal cost optimization.
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Extreme consolidation in healthcare payers and providers creates monopolistic pricing inefficiencies that stifle market competition and inflate costs.
Impact: Fragmenting consolidated entities could restore competitive pricing and drive systemic cost reductions across the industry.
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AI token costs are exploding but remain vastly cheaper than human labor for back-office tasks, justifying massive investment in model usage over headcount.
Impact: Shifting budgets from labor to AI compute enables companies to achieve superior ROI and scale operations exponentially.
Action items
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Audit current SaaS subscriptions and identify high-friction, low-differentiation tools that can be replaced with custom AI agents or open-source alternatives.
Impact: Reduces recurring software expenses and eliminates administrative bottlenecks, freeing engineering resources for core product development.
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Deploy AI agents for routine outreach, negotiation, and contract management, while reallocating human staff to complex relationship building and strategic oversight.
Impact: Increases sales and contracting throughput by 10x while maintaining high-touch service for premium clients.
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Establish an "agent supervisor" team to manage AI-generated exceptions, approvals, and strategic deviations, ensuring quality control without manual intervention.
Impact: Maintains operational integrity at scale while allowing automated systems to handle high-volume routine tasks efficiently.
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Restructure back-office workflows to prioritize AI-driven volume expansion rather than pure headcount reduction, leveraging automation to capture new market share.
Impact: Transforms cost-saving initiatives into revenue-growth engines by unlocking previously unattainable operational scale.
Quotes
“We're cutting about 80% of our SaaS spend this year... we have an internal CRM that was vibe-coded, that is working better, that is managing our process better.”
“If you ask them to 10x capacity, that's literally the opposite of what they're built for... you've got to find other ways of doing the testing using supplies that maybe wouldn't traditionally be used.”
“We've not said, okay, we're doing 100 a week, so we'll get the agent to do 100 a week. What we've done is said, well, now that we have the agent, we can do 10 times as many contracts this year.”