Full disclosure: we're Ryz Labs, and we're on this list. So yes, we're biased. Here's what we'd actually tell a friend, including when you should hire someone else.
Most enterprise AI work doesn't fail at the demo. It stalls between the pilot and production, where the system has to run on live data, in your cloud, under your security rules, with someone accountable when it breaks. The question that decides this choice: who builds the system, where does it run, and who owns it once it's live?
A pilot can live in a notebook. A production system has to pass security review, connect to systems of record, handle bad inputs, and keep working after the people who built it move on. Enterprise buyers rarely lack ideas. They lack a team that can carry one idea all the way into production inside their own environment.
That makes three things matter more than headline scale. First, where the system runs: in your cloud and repos, or on a vendor platform you will depend on. Second, who is accountable: one team with a name, or a program spread across workstreams. Third, how you pay: per person, per output, or per program, and whether you can budget it before you start.
If you're in the first group, our pages on AI implementation and partners to take an AI pilot to production go deeper.
We build AI pod teams: senior engineers you meet by name before the engagement starts. They work on your team, in your repos, your cloud and your standups, and report to your leads. A typical pod is about seven people, including a tech lead, an ML engineer and backend engineers, working as one accountable team. They build on what you already use, such as AWS, Azure, GitHub, Postgres, and Anthropic and OpenAI models. There's no Ryz platform to adopt, and you own all the code and IP. Only the top 1% of the tens of thousands of engineers we interview make it, and a pod can start in under two weeks once you say go.
The price is public. A pod of five senior engineers runs about $50,000 to $75,000 a month, with a tech lead quoted per team. Our pods have shipped production work: fraud detection for a global fleet company ($5.94M in confirmed fraud, 244K+ invoices scored), marketing compliance review for a leading alternative asset manager (8,000+ documents, days to hours), and a driver-support agent covering about 218,000 calls a year. See our case studies.
Where we're not the right fit: if procurement needs a consumption-priced SKU, we price per engineer instead. If you need engineers in Europe or Asia time zones or follow-the-sun coverage, a global network fits better. If you want a board-level transformation program, management consulting or a proprietary AI platform, look at the integrators below.
Accenture reported $74.2B in FY2026 revenue and about 814,000 people. In December 2025 it formed the Accenture Anthropic Business Group, with about 30,000 professionals to be trained on Claude, including forward-deployed engineers it calls "reinvention deployed engineers." It also has its AI Refinery platform.
Where it beats us: breadth. Consulting, managed services and engineering under one firm, in 52 countries, with 350+ ecosystem partners. The catch: you are buying a program from a very large firm, so ask who will be on your account day to day. See our Accenture alternatives.
Globant describes AI Pods as "human-supervised delivery units that combine documented workflows, AI agents and expert supervision." On October 27, 2026 it added Glob.AI OS, a governance layer that it says runs as SaaS or in the client's own cloud. Software Pods are billed per supervised token for approved output. Globant had 27,411 Globers at the end of Q2 2026.
Where it beats us: a catalog procurement can buy from, and a model where you pay for approved output instead of people. The catch: agents do the work, and your cost depends on volume you learn after you start. See Globant AI Pods vs Ryz AI pods.
Thoughtworks has three decades of engineering-led consulting. In 2026 it launched AI/works, an agentic development platform tied to a delivery model it describes as a path "from idea to production in 90 days," and Agent/works, a control plane for running agents in production.
Where it beats us: its own platforms for modernization and agent governance, plus analyst recognition from Forrester and Gartner. The catch: both platforms are 2026 launches, and New York overlap depends on which office staffs the work. See Thoughtworks alternatives.
EPAM reported $5.457B in FY2025 revenue and about 56,600 delivery professionals. It sells AI/Run.Transform, consulting built around blueprints for AI-native teams, and the open-source DIAL orchestration platform. In 2025, 64.4% of its revenue came from clients of five years or more.
Where it beats us: scale and staying power across many workstreams at once. The catch: delivery is weighted toward India and Central and Eastern Europe, so overlap with US Eastern hours depends on the team. See EPAM alternatives.
Turing's core business supplies training data and evaluations to frontier AI labs. Its enterprise line, Turing Intelligence, offers Advise, Augment and Build, delivered by pods and forward-deployed engineers. Turing says clients keep their code and IP.
Where it beats us: depth at the model layer. The catch: enterprise build is its newer line, and time-zone overlap depends on who is staffed.
If you have a pilot that needs to run in production in your own stack: Ryz Labs. Named senior engineers, New York hours, your cloud and repos, a public price, and a start in under two weeks once you say go.
If you need one firm to run a global program across many business units: Accenture.
If you'd rather buy approved output than people: Globant.
If you're modernizing a large legacy estate with a consulting partner: Thoughtworks or EPAM.
Regulated teams can also read our page on financial services AI engineering.
It designs, builds and ships AI systems, such as agents, document review or fraud models, into your production environment. The big differences are who does the work (your team plus theirs, their program team, or agents) and where the system runs.
Most firms don't publish prices. Ours is $7,000 to $15,000 per engineer per month, so a pod of five senior engineers is about $50,000 to $75,000 a month. See engineer rates by role.
It depends on the system and your security process. The first step is having the right team in place: ours can start in under two weeks once you say go.
It can help for repeatable tasks. Just know what you'd have to migrate off later. We build in your stack with no platform to adopt. Our Globant alternatives and AI pod providers guides compare both approaches.
With us, yes. You can add people as the work grows, or have the pod hand the whole system to your team when it's done.
We checked pricing and services for every provider here in October 2026. This changes often, so double-check before you sign anything.
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