AI-native service businesses are reshaping professional services. Instead of selling tools, they deliver outcomes — fusing automation with expert labor to execute complex workflows at scale. Build is defining this model in real estate development; OffDeal is reinventing investment banking; Crosby and EvenUp are reprogramming the legal industry. Together, they represent a new category: software-delivered services — where AI handles the work and humans handle the exceptions.
1. The Professional Services Revolution
For decades, professional services ran on one equation:
More people = more output.
Law firms, consultancies, engineering firms, and banks grew linearly — scaling headcount to match demand. But in 2025, that model is breaking.
AI-native services are emerging as the new paradigm — businesses built from the ground up to automate their own workflows.
They don’t sell software for clients to operate.
They deliver finished work products — powered by autonomous systems, guided by experts, and billed for outcomes.
This software-delivered services model is quietly redefining entire industries — from development and law to finance and healthcare.
2. Defining AI-Native Services
An AI-native service company merges:
Agentic automation — AI workflows performing structured tasks end-to-end.
Expert oversight — professionals who review, verify, and own quality control.
Outcome-based delivery — clients buy results, not dashboards.
In short:
Traditional SaaS sells access.
AI-native services sell completion.
This model blends software economics (scale, margin, data feedback loops) with service trust (domain expertise, compliance, and accountability).
| Dimension | SaaS | AI-Native Service |
|---|---|---|
| Setup Time | Weeks–months | Immediate |
| Ownership of Execution | Client | Vendor |
| Deliverable | Tool | Completed workflow |
| Billing | Seat/license | Output or SLA |
| Value Promise | “Use this tool” | “We’ll do the work” |
3. Build and the Future of Development Services
Automating the Built World
Build exemplifies the AI-native model in the real estate and infrastructure sector — a $200B annual services market historically untouched by automation.
Founded in 2024, Build pairs a high-tech, high-touch approach — expert architects and developers working alongside AI agents that automate site selection, legal review, permitting, and design.
Key numbers:
90% faster output than traditional workflows
Clients totaling nearly $2 trillion AUM
Expansion across San Francisco, London, and New York
Where legacy AEC giants like AECOM and WSP rely on armies of consultants, Build operates with a lean core — “more agents than people.”
Why it matters:
Build isn’t selling a development platform. It’s selling development itself — delivered through software. Each new workflow automated adds eight figures of serviceable market spend, creating compounding growth.
4. The Broader Shift: From Software to Software-Delivered Services
The last two decades saw software eat the world.
The next decade will see software deliver the world.
Across industries, we’re seeing a convergence:
Clients demand deliverables, not dashboards.
Automation can execute expert workflows at human parity.
The best results come from hybrid human-AI teams.
This new architecture allows firms to scale like software, charge like services, and deliver like consultants.
5. Banking & Finance: From Advisory to Autonomous Execution
Case: OffDeal — The AI-Native Investment Bank
OffDeal is pioneering this model in investment banking. Its platform automates M&A workflows — buyer matching, diligence, and deal preparation — allowing small business owners to complete transactions that once required full teams of analysts.
What makes it AI-native:
AI performs 80% of the analytical workload.
Human bankers oversee valuation, negotiation, and compliance.
Clients pay for closed deals — not access to a CRM or marketplace.
Impact:
OffDeal is democratizing investment banking for the lower mid-market — where traditional firms can’t profitably operate. The result is a software-delivered service that runs Wall Street workflows without Wall Street overhead.
Other AI-native finance examples:
Pagaya Technologies — AI underwriting for lenders and credit platforms.
Gradient Labs — UK-based AI fraud investigation services for fintech.
Each points to the same trajectory — financial services are shifting from manual expertise to autonomous advisory.
6. Law: The Next Frontier of AI-Delivered Expertise
Crosby — Legal Ops Reimagined
Crosby delivers end-to-end legal workflows — from drafting to filing — via a hybrid AI-human model. Its system acts as an “AI paralegal,” automating research and document generation while expert attorneys validate every output.
Result:
40× throughput increase in legal operations.
Compliance embedded through human review.
EvenUp — Outcome-Based Legal Automation
EvenUp automates personal injury demand letters — one of the most repetitive and labor-intensive tasks in law.
Why it works:
Trained models predict settlement values and write persuasive drafts.
Legal reviewers guarantee accuracy and tone.
Firms 10× their case throughput with no drop in quality.
Together, Crosby and EvenUp show how AI-native services can scale law the way SaaS scaled marketing — by codifying expert logic into repeatable workflows.
7. Insurance & Risk Services: Automating Trust
Insurance sits at the intersection of data and liability — perfect terrain for software-delivered services.
Emerging models:
Claims Processing as a Service — AI triages, experts adjudicate.
Fraud Detection as a Service — Agentic systems flag anomalies, humans validate.
Underwriting Automation — AI builds risk models, human actuaries review.
These firms promise outcomes — “decision-ready claims in 24 hours” — rather than software licenses. That shift, from tool to guarantee, is the hallmark of AI-native services.
8. Healthcare and Life Sciences: Outcome-Based Intelligence
Healthcare is following fast.
AI-native firms are emerging across:
Clinical documentation automation (AI pre-processes notes, clinicians approve).
Trial operations (protocol design, regulatory submissions).
Medical billing and claims (end-to-end managed services with AI verification).
Each model follows the same architecture:
AI handles the volume.
Experts ensure compliance.
Clients receive verified results.
In regulated spaces where accuracy is existential, AI-native services outperform pure AI tools precisely because they retain human accountability.
9. The Architecture of AI-Native Businesses
The Four-Layer Stack
Foundation Models: Fine-tuned for domain specificity (CRE data, legal filings, medical codes).
Agentic Orchestration: Multi-step, goal-directed automation across datasets and APIs.
Expert-in-the-Loop Systems: Human professionals validate, override, or annotate AI outputs.
Outcome Delivery Layer: Outputs rendered as documents, reports, or API calls — delivered as a finished service.
This layered design allows one expert to supervise hundreds of concurrent workflows — flipping the traditional labor ratio.
Example: Build aims to have “more agents than people” by 2026 — achieving exponential operational leverage.
10. Economics and ROI: Why This Model Wins
| Metric | Traditional Services | AI-Native Services |
|---|---|---|
| Output per employee | 1× | 10–100× |
| Cycle time | Weeks–months | Hours–days |
| Gross margin | 20–30% | 60–80% |
| Scalability | Linear | Exponential |
| Customer retention | Moderate | High (embedded in workflows) |
This hybrid approach yields SaaS-like margins with consulting-level stickiness.
Every delivered workflow improves the models beneath it — compounding efficiency over time.
11. Guardrails: Compliance, Quality, and Trust
No automation model can succeed without human validation, governance, and auditability.
AI-native firms build trust through:
Compliance frameworks (ISO 27001, SOC 2, GDPR).
Traceable agent actions with versioned output logs.
Explainable AI for regulators and enterprise buyers.
The winning playbook is human-supervised autonomy — not unchecked automation.
12. Should You Transition to an AI-Native Model?
If your business:
Owns repeatable workflows,
Has access to proprietary data, and
Employs domain experts…
…then you’re positioned to evolve into a software-delivered service.
ROI Decision Matrix
| Evaluation Criteria | Weight | Example KPI |
|---|---|---|
| Workflow repeatability | 30% | % automatable tasks |
| Data richness | 25% | Historical dataset size |
| Regulatory clarity | 20% | ISO/SOC/GDPR alignment |
| Client outcome visibility | 15% | SLA adherence rate |
| AI & expert talent access | 10% | Agents per expert |
Typical uplift: 5–10× productivity gain, 2–3× margin expansion, near-zero onboarding friction.
13. The Future of Professional Services
By 2030, most service work will be AI-augmented, outcome-delivered, and software-scaled.
In real estate, Build is transforming development into an autonomous, data-driven process.
In banking, OffDeal is rebuilding investment workflows from code.
In law, Crosby and EvenUp are scaling judgment itself.
These are not software companies or consultancies.
They are AI-native service institutions — new operating systems for expertise.
14. Conclusion: The New Delivery Paradigm
The professional services industry is moving from:
Selling hours → to selling outcomes.
Selling software → to delivering services via software.
This new generation of companies doesn’t just digitize human labor — it compounds it.
Each task completed trains the system.
Each workflow automated expands the market.
Each deliverable shipped proves the model:
Software-delivered services are the future of work.
FAQ: AI-Native Services and the Future of Expertise
What is an AI-native service business?
A company that uses AI agents and human experts to deliver completed work products — not just tools — as a managed service.How is this different from SaaS?
SaaS gives you the tool; AI-native services deliver the output. They take operational ownership and provide outcomes under SLAs.Which companies are leading this model?
Build (development automation), OffDeal (AI-native investment banking), Crosby (legal ops), and EvenUp (legal brief generation).What industries are best suited?
Real estate, banking, law, insurance, and healthcare — any workflow that’s structured, repeatable, and high-value.What are the main risks?
Regulatory compliance, data integrity, and over-automation. The best firms use expert-in-the-loop systems to mitigate these.How do AI-native firms maintain trust?
Through ISO/SOC certifications, transparent audit trails, and expert validation for every AI-generated output.What’s the economic upside?
10× throughput, 2–3× margins, and exponential scalability once workflows are codified.How can legacy firms adapt?
Wrap AI and expert oversight around existing services — delivering results, not reports.What’s next?
By 2030, most professional services firms will either be AI-native or powered by one.