Quick note before we start: this was written by Ryz Labs, and we're one of the options below. We're biased, so we've been straight about where others beat us.
Choose Ryz if you're a US enterprise, in any industry, that wants a senior AI pod team working inside your cloud and repos, on US hours, shipping an AI system to production. We're trusted by Fortune 500 engineering teams, and our pods have done exactly that, including a fraud detection system with $5.94M in confirmed fraud and a compliance review system that has processed 8,000+ documents for a global capital management firm.
Choose Turing if your problem lives at the model level (fine-tuning, evaluation, post-training), where its frontier-lab data business gives it real depth, or if you need to scale AI talent quickly from a very large global pool.
Model-level depth. Turing's core business supplies data and evaluation to frontier labs such as OpenAI, Google, Anthropic and Meta, according to Sacra. That work gives it real depth in post-training and evaluation. If your project is about how a model behaves (custom evaluation suites, fine-tuning, measuring quality), Turing is closer to that problem than we are.
A very large talent pool. Turing says it has a network of more than 4 million engineers and experts. If you want to pull rare AI specialists from many countries at once, Turing's global network is built for that.
Clear phases for pilot to production. Turing's Build offering starts with rapid prototyping to test feasibility and ROI, then moves to production engineering with KPIs set on day one. It also says clients keep their code and IP and that there is no vendor lock-in.
Capital and momentum. A $2.2B valuation and a large frontier-lab business give Turing resources to invest in its own model-evaluation tooling.
Our pods ship to production. One Ryz pod built AI fraud detection for a global fleet company: 244K+ invoices scored, under 30 seconds per invoice, and $5.94M in confirmed fraud, validated by the client's own fraud team. Another built AI marketing compliance review for a global capital management firm that has processed 8,000+ documents and cut review from days to hours. Others built an AI voice platform that has handled 1M+ outbound calls. Client names stay private; the details are on our case studies page.
A senior pod inside your cloud and repos. A typical pod is about 7 senior engineers, including a tech lead, an ML engineer and backend engineers, working as one team. They work in your repos, your CI and your standups, inside your cloud (AWS, Azure, GitHub, Postgres, with Anthropic and OpenAI models), and show working software in weekly demos.
New York hours. Our engineers are in Latin America and work within about an hour of US time zones, so code review and decisions happen the same day. Turing delivers from a distributed global network, and public forward-deployed engineer postings include Hyderabad, India, so overlap depends on who gets staffed.
You choose the engineers. We've interviewed tens of thousands of engineers, and only the top 1% make it. You get a recruiter-curated shortlist, you run the final interview, and our quote comes with the names of the people who would do the work. See our vetting process.
You own the result. When the system is running, you can grow the pod with more people or disciplines, or have it hand the whole system over to your team. The code and the know-how stay with you.
A stable team, and enterprise build is our main job. Our pods are a fixed group that stays with your system. Sacra reports Turing's growth came mainly from frontier-lab work, so enterprise build is a newer line for it.
Where we're not the right fit. If your work is model training, evaluation or post-training research, Turing is the better pick. The same goes if you want a self-serve, hourly marketplace for short gigs, engineers in Europe or Asia time zones, or published, self-serve pricing before a conversation.
Turing doesn't publish prices for Turing Intelligence, its pods or its forward-deployed engineers. You'll need to talk to their team.
Ours is a custom quote, scoped per team. We scope first because a pod sized for one pilot looks different from a pod running several connected systems. You get a scoped plan, a price and the names of the people who would do the work. Neither of us lets you compare a public number, so ask both for a written scope you can lay side by side.
Comparing more firms that use forward-deployed engineers? See the best forward-deployed engineering firms, our Turing alternatives, or Ryz Labs vs Tribe AI.
Not mainly. Its core business is supplying training data, evaluations and RL environments to frontier AI labs (per Sacra). Turing Intelligence, its enterprise build line, is newer and uses pods and forward-deployed engineers.
It sells "Intelligence for BFSI" and reports anonymized results on its site, including a 45% cut in underwriting timelines and audit prep time cut by 50%. We didn't find a named financial institution client. Its job postings say it serves Fortune 500 enterprises in financial services.
Public postings we found include Hyderabad, India (hybrid). US-based roles show up on job aggregators, but we couldn't verify locations. Ask Turing where your specific team would sit.
Yes. Our pods work in your stack with your vendors, including models from Anthropic and OpenAI. If you have model evaluation work elsewhere, the pod can build the production system around it. Talk to us about scope.
We checked every provider on this page in October 2026. If something has changed, tell us and we'll update it.