AI Factory

Take control of

your AI future

If tokens were free, what would you do?

Most enterprises are renting their reasoning indefinitely, on a meter they don't control, and outsourcing their intelligence. We help you fix that. Wherever you are on the maturity curve, from first frontier API calls to on-prem models served at scale, Thoughtworks delivers the strategy, architecture, and hands-on capability to build an AI Factory, with an AI operating model you own.

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$37b spent on enterprise GenAI in 2025 — 22x growth in just two years. The bill arrived before the ROI.

63% of enterprise organizations are already using open source models.

96.6% cost reduction with open models vs. frontier models on non-frontier tasks.

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Stage 0

Rent the frontier

Most organizations start here, using premium AI models to accelerate experimentation and prove value. However, as adoption grows, costs can rise quickly because every workload uses the most expensive intelligence.

Best for: Early AI adoption and experimentation

Stage 1

Rent alternative intelligence

Leading organizations reduce AI costs by matching each workload to the right model. Routine tasks often achieve the same outcomes with lower-cost models, without sacrificing quality.

Best for: Scaling AI while controlling costs

Stage 2

Rent the hardware

As AI usage grows, infrastructure becomes the next opportunity for savings. Running models on dedicated GPU infrastructure lowers costs further while increasing flexibility and performance.

Best for: High-volume enterprise AI

Stage 3

Own the hardware

Organizations with AI at the core of their business gain maximum control, predictable economics and full data sovereignty by owning their AI infrastructure. The tradeoff is greater operational responsibility.

Best for: Mission-critical AI platforms

~80% of companies sit at Stage 0, while the highest ROI awaits at Stage 1 and Stage 2.

How we help clients

Optimize what you spend today. Your AI bill is scaling faster than the value. Matching the right model to the right workload, not the most expensive one for every job, is how you improve AI unit economics and create room to do more.

Our promise: We maximize the return on every AI dollar by identifying which workloads can move to cheaper models without compromising quality. And we bring the numbers to show the CFO.

Build the right plan for what’s next. The window to build a deliberate hybrid AI strategy is closing. Infrastructure, power, and AI adoption are moving faster than enterprise planning cycles. Organizations that build the roadmap now will have options. The ones that wait will inherit constraints

Our promise: We help organizations understand where they are on the AI maturity curve and build the roadmap, architecture, and operating model to move forward with confidence.

Own your AI capability long term. Every task you route through a proprietary API deposits into someone else's learning loop, not yours. The model improves and the vendor captures the value — that's dependency, not strategy. The organizations that will win aren't just cutting costs. They own the learning loop: the models, the data, the feedback, and the direction.

Promise: We help organizations reduce vendor dependency, improve governance, and build an AI architecture that keeps models, data, decisions, and the learning that compounds them inside the organization.

Our promise: We maximize the return on every AI dollar by identifying which workloads can move to cheaper models without compromising quality. And we bring the numbers to show the CFO.

Our promise: We help organizations understand where they are on the AI maturity curve and build the roadmap, architecture, and operating model to move forward with confidence.