# Top 10 AI and SI (Super Intelligence) Development Companies in the USA for 2027

URL: https://vrisic.com/blog/top-10-ai-and-si-development-companies-usa/
Last updated: 2026-10-18

**Short answer:** There is no single top ten, only the right firm for your size, cloud and risk. For large and regulated programmes look at ScienceSoft, Thoughtworks, Globant, EPAM and IBM Consulting. For mid market agent work look at HatchWorks AI, Master of Code Global and Tribe AI. Loka suits AWS teams, and Ode with Anthropic suits mid size firms standardising on Claude. “SI” is a federal naming change, not a different product, so judge each firm on evaluation, ownership terms and price. Facts dated October 2026.

In this guide

1. The shortlist at a glance
2. AI and SI: how to read this list
3. How we chose these ten
4. Large and regulated programmes
5. Mid market and agent specialists
6. Cloud and model specialists
7. Where Vrisic fits (listed separately)
8. Which firm for which situation
9. One question to put to each firm
10. What US AI developers charge
11. Worked example: same project, three routes
12. How to choose
13. Diligence questions that separate firms
14. Mistakes buyers make with lists like this
15. Red flags
16. How Vrisic can help
17. Sources

Searches for the top AI companies in the USA now come with a second term: SI, short for Super Intelligence, after the 29 September 2026 federal order. This page lists ten companies with US operations, states what each says about itself, says who each one suits and who should look elsewhere, and notes what is published about price. Read our [explainer on AI vs SI](https://vrisic.com/blog/ai-vs-si-super-intelligence-us-businesses/) if the new wording is unfamiliar, and our comparison hub for side by side pages with Vrisic.

Disclosure: Vrisic wrote this page; we are a competitor, so check every claim against the sources. Vrisic is not ranked among the ten companies below. We use only facts from the public sources listed at the end, dated October 2026, and we say where the other company is the better choice.

## Top 10 AI and SI development companies in the USA at a glance

The order follows buyer type, not a ranking. We do not score or rank companies against each other, because public pages cannot show delivery quality.

| Company | US base | Suits | Does not suit | Published pricing |
| --- | --- | --- | --- | --- |
| ScienceSoft | McKinney, Texas | Healthcare, insurance and enterprise buyers who want a long established vendor | Anyone wanting a firm price without scoping | Bands from $10,000 to $1,000,000 or more |
| Thoughtworks | Chicago | Large firms modernising old systems while adding AI | Small budgets | Not published |
| Globant | New York | Continuous, subscription based AI assisted delivery | A single fixed scope project | Subscription, metered; amounts not published |
| EPAM Systems | Newtown, Pennsylvania | Enterprises running several GenAI products | One small pilot | Not published |
| IBM Consulting | Armonk, New York | Regulated hybrid cloud estates and US public sector | Teams avoiding IBM tooling | Not published |
| HatchWorks AI | Atlanta, Chicago, Dallas | Mid market and enterprise teams wanting an agent programme plus capacity | A small fixed scope pilot | Not published |
| Master of Code Global | Redwood City, California | Brands with customer facing conversational agents | Back office only | Pilot price not published |
| Tribe AI | New York, San Francisco | Large US companies whose pilots never reached production | Buyers needing a price up front | Not published |
| Loka | Los Altos, California | Startups and scaleups on AWS and Amazon Bedrock | Azure or Google Cloud shops | Not published |
| Ode with Anthropic | San Francisco | Mid size firms that have chosen Claude | Buyers wanting a model neutral partner | Not published |

## AI and SI: how to read this list

None of these companies sells a system smarter than people, and none claims to in the sources we checked. When a company markets its work as SI, it means the same agents, models and platforms it sold as AI. For federal work, ask which definition of SI the agency uses and whether the company can meet it; IBM, for instance, states that its IBM Consulting Advantage delivery platform is FedRAMP authorised and available on AWS GovCloud (US), which matters to federal buyers whatever the label. For private work the old and new terms mean the same thing, so judge the engineering. Our guide to choosing an SI development company has the questions to ask.

## How we chose these ten

The aim was a list a US buyer could use as a starting shortlist, covering different sizes and delivery models, with every statement traceable. We applied four tests and recorded what we found.

1. **US presence.** The company states a US headquarters or US offices on its own site or in a public release.
2. **Real AI delivery.** Its pages describe building AI systems such as agents, retrieval, models or platforms, not only advisory slides.
3. **Traceable facts.** Everything below comes from the company’s own pages or a named press release. We write “not published” where a price is missing and we do not estimate it.
4. **Spread of models.** We wanted fixed project vendors, subscription capacity, embedded engineers, platform led consultancies and cloud or model specialists, so the list teaches the differences.

What we did not do: we did not use client review scores to rank, we did not take payment for placement, and we did not judge technical quality. Self reported figures such as client retention rates are labelled as the company’s own. Firms left out are not judged worse; a list of ten cannot cover the market. If a firm you rate is missing, our guides to [best AI software development companies](https://vrisic.com/blog/best-ai-software-development-companies/) and [top AI agent development companies](https://vrisic.com/blog/top-ai-agent-development-companies/) cover others.

What the ten say about themselves, in numbers. Sources: company pages and releases read October 2026. Figures are the companies’ own, not independently audited.

## Large and regulated programmes

These five suit organisations that need audit trails, procurement frameworks, many systems at once or a delivery partner that is very unlikely to disappear. The trade-off is price opacity and process weight.

### ScienceSoft: best for US buyers who want published cost ranges

ScienceSoft gives McKinney, Texas, in the Dallas area, as its US address, says it was founded in 1989 and reports over 750 IT professionals, with offices in North America, Europe, the UK and the Gulf. It states ISO 9001, ISO 27001 and ISO 13485:2016 certifications and says it has delivered more than 4,300 IT projects for clients in over 80 countries. Its AI work spans strategy, end to end development of GenAI, agents, multi agent systems and predictive ML, adding AI to existing software, custom MCP servers, agentic quality assurance and security work.

It publishes three cost bands: $10,000 to $100,000 for a chatbot or conversational agent, $50,000 to $150,000 or more for an agent that connects to enterprise systems and acts with approvals and guardrails, and $300,000 to $1,000,000 or more for systems with several AI components. It offers a proof of concept, an MVP or a full build, and a free, non binding ballpark estimate within 24 hours. It says cost and timeline are fixed only after a questionnaire or discovery, and it does not publish standard timelines.

**Best for:** healthcare, insurance and enterprise buyers who want a long established vendor with certifications. **Keep in mind:** bands are wide, so push for a scoped estimate and ask which band your system falls in.

### Thoughtworks: best for enterprise modernisation with AI built in

Thoughtworks is headquartered in Chicago and was taken private by Apax Partners in 2024. Its AI offer covers AI strategy (maturity assessments, token economics and value roadmaps), agentic AI built on its AI/works development platform, AI factory services for hosting models on your own hardware in cloud or on premises, and data modernisation. On 16 June 2026 it launched Agent/works, which it describes as a single control plane and governed runtime for AI agents on any cloud. According to the launch release, the platform checks an agent’s possible workflow paths for at least one compliant route before it runs, grants scope limited, time limited permissions, and keeps a central registry of agents, models, tools and policies with evaluations and cost controls.

Its site cites a 60% faster build for the Antibiogo app used by Médecins Sans Frontières across 100 or more labs and a 90% reduction in manual data search for a life sciences client; these are the company’s own case figures. It lists partnerships with AWS, Google Cloud, Microsoft, Databricks and Nvidia.

**Best for:** large firms modernising core systems while governing many agents. **Keep in mind:** senior consulting teams carry enterprise rates and no prices are published. Our Thoughtworks vs Vrisic page sets out the contrast.

### Globant: best for subscription based AI engineering

Globant, which gives New York as its headquarters, launched AI Pods on 5 June 2025. At that date it reported over 31,100 employees in 36 countries. Clients subscribe monthly and receive token based, metered capacity covering engineering, product definition, design and testing, delivered on its model agnostic Globant Enterprise AI platform and a code agent called CODA. The release promises “faster time to market and lower costs” but gives no prices, tiers or token quantities.

**Best for:** companies with a long stream of AI work who prefer capacity on tap to separate projects. **Keep in mind:** ask how token capacity maps to real features and what happens to unused capacity. A subscription that is cheap per month can be expensive per shipped feature. See Globant vs Vrisic.

### EPAM Systems: for large multi product programmes

EPAM’s releases are datelined Newtown, Pennsylvania. It offers LLM research and advisory, rapid proof of concept and MVP delivery, and full transformation programmes. Its DIAL platform, released as open source under the Apache 2.0 licence in December 2023, is a multi modal, model agnostic workbench that is containerised and Kubernetes ready, with monitoring and troubleshooting tools. EPAM said it used DIAL in more than 500 use cases and that it runs in production on all major public clouds.

**Suits:** enterprises running several GenAI products at once that value an open source orchestration layer they can inspect. **Look elsewhere if:** you have one small pilot. Pricing is not published.

### IBM Consulting: for regulated firms on hybrid cloud

IBM Consulting builds agents on watsonx, with watsonx Orchestrate managing many agents in one place. On 6 May 2026 it announced Context Studio, for agents grounded in the structure of an organisation’s data and processes, and said IBM Consulting Advantage is FedRAMP authorised and available on AWS GovCloud (US). IBM cites Providence, the US health system, which built an HR agent on watsonx Orchestrate connected to its existing HR platform; after about eight months IBM reports managers spent 90% less time on hiring steps and time to fill positions fell 60%. Those are IBM’s figures about a client, not independent results.

**Who it suits:** government, healthcare and financial groups with mixed on premises and cloud estates. **Who should look elsewhere:** teams that want to stay free of IBM tooling. Pricing is not published.

## Mid market and agent specialists

These firms sell agent delivery to mid size and large companies, often with engineers embedded in your team. Fit depends on whether you want a pilot, capacity or a programme.

### HatchWorks AI: for embedded nearshore engineering

HatchWorks AI lists offices in Atlanta, Chicago and Dallas in the US and in San José (Costa Rica), Medellín and Lima, and says it combines US and nearshore engineering across the Americas. It sells three models: Forward Deployed Engineers who embed in your teams from day one, Agentic AI Pods that it says replace a team of 8 to 12 with AI doing execution while humans direct and validate, and a full AI and Data Transformation Program owned by one accountable team. It reports 97% client retention and a 4.9 out of 5 rating from 29 verified Clutch reviews; both are its own published figures. No prices are listed.

**Who it suits:** US mid market and enterprise teams that want an agent programme plus capacity in familiar time zones. **Who should look elsewhere:** buyers who want a small fixed scope pilot with a set price. See HatchWorks AI vs Vrisic.

### Master of Code Global: for customer facing conversational agents

Master of Code Global works from Redwood City, California and Winnipeg, Canada. Its agent service covers architecture, CRM and ERP integration, evaluation, guardrails, human in the loop review and lifecycle management. In a post dated 29 May 2026 it formalised an AI pilot: 30 days on a fixed budget set from day one, with a discovery phase that assesses technical fit, compliance, security and ROI, then a proof of value build against success criteria agreed at the start. Deliverables include an analytics instrumented solution, KPI results, improvement recommendations and an architecture roadmap for the next phase.

**Who it suits:** retail, telecom, travel and banking brands whose agents talk to customers at volume. **Who should look elsewhere:** teams that only need back office automation. The pilot price is not published, so get it in writing. See Master of Code Global vs Vrisic.

### Tribe AI: for stalled Fortune 1000 pilots

Tribe AI calls itself an AI native services company with offices in New York, San Francisco and Lisbon. It targets Fortune 500 and Fortune 1000 enterprises, embeds forward deployed engineers with client teams to turn architects’ designs into production systems, and says it partners closely with OpenAI and Anthropic. It states SOC 2 Type II certification and Microsoft SSPA compliance and says client data and the AI built on it stay inside the client’s environment. Its pages in our reading gave no client counts, headcount or prices.

**Suits:** large US companies whose pilots never reached production. **Look elsewhere if:** you need a firm price before work starts.

## Cloud and model specialists

### Loka: for companies built on AWS

Loka lists a Silicon Valley office in Los Altos, California. It states it is an AWS Premier Tier Services partner holding the Generative AI Services Competency and the Agentic AI Specialization, plus DevOps, Healthcare, and Data and Analytics competencies, and says it was named an AWS Partner of the Year in 2024. Its site describes AWS funded programmes, for example a GenAI Workshop that is 75 to 100% AWS funded over 4 to 10 weeks and a GenAI Launchpad for startups that is 100% AWS funded over 3 to 4 weeks, and says AWS can fund up to 50% of its services in cash. These are Loka’s own statements about eligibility, so confirm what applies to you with AWS.

**Suits:** startups and scaleups that want Amazon Bedrock done properly and may qualify for funding. **Look elsewhere if:** you run on Azure or Google Cloud.

### Ode with Anthropic: for mid size firms standardising on Claude

Ode was introduced on 15 July 2026 by Anthropic, Blackstone and Hellman & Friedman as an enterprise AI services firm, with further investors named in the release including Goldman Sachs, General Atlantic, Apollo, GIC and Sequoia Capital; no investment amounts were given. It is built on Fractional AI, an applied AI services firm acquired in May 2026, and led by Fractional’s co-founders, Chris Taylor as chief executive and Eddie Siegel as chief technology officer. It combines Anthropic’s models with its own AI engineers and operators and says it serves mid size companies and other enterprises in financial services, healthcare, retail, manufacturing and software.

**Who it suits:** mid size firms that have chosen Claude and want vendor backed engineering. **Who should look elsewhere:** buyers who want a model neutral partner, and anyone who needs a long delivery history, since the firm launched in 2026. Pricing is not published.

## Where Vrisic fits (listed separately)

Vrisic is a young custom AI software company with a remote team based in India that works US, UK and UAE business hours. We have no local offices and no long client list to show you. What we offer is a clear deal: one fixed price in writing after a free scoping call, the build running in your cloud account with your model provider keys, you owning the code, prompts and test data, and no per seat licence fees.

Typical Vrisic ranges: a single task agent $8,000 to $25,000 over 3 to 6 weeks, an integrated multi channel agent $25,000 to $60,000 over 6 to 10 weeks, and a multi agent system $60,000 to $150,000 or more over 10 to 16 weeks. Hosting and model usage are extra and billed at cost. Our [agent cost guide](https://vrisic.com/blog/ai-agent-development-cost/) explains what moves a project between tiers. We suit US companies that want one defined system, a fixed price and full ownership. We do not suit programmes that need on site teams in many US cities, certifications we do not hold or a long list of Fortune 500 references.

## Which firm for which situation

Most buyers know their situation better than they know vendors. Start from the row that matches you, then read the matching profile above.

| Your situation | Start with | Why |
| --- | --- | --- |
| Federal or state agency buyer | IBM Consulting, ScienceSoft | IBM states FedRAMP authorisation for its delivery platform; ScienceSoft states ISO 27001 and HIPAA compliance |
| Healthcare or insurance, long vendor history needed | ScienceSoft | Founded 1989, ISO 13485:2016 stated, published cost bands |
| Core system modernisation plus agents | Thoughtworks, EPAM | Platform and governance tooling for many agents |
| Customer facing agent at volume | Master of Code Global, HatchWorks AI | Evaluation, guardrails and a defined pilot |
| Stalled enterprise pilot | Tribe AI, HatchWorks AI | Embedded engineers and a production focus |
| Everything already on AWS | Loka | AWS competencies and funded programmes |
| Committed to Claude, mid size | Ode with Anthropic | Vendor backed and Claude specific |
| One defined system, fixed price, own the code | Vrisic or ScienceSoft | Written price after scoping, project delivery |

## One question to put to each firm

Generic questions get generic answers. These are the specific questions we would ask each company, based on what its own pages emphasise. They are our suggestions, not allegations that any firm falls short.

- **ScienceSoft:** which of your three cost bands does my system fall in, and what does the 24 hour ballpark leave out?
- **Thoughtworks:** do I need Agent/works and AI/works, or can the work run on tooling I already own?
- **Globant:** what does one pod month buy in shipped features, and what happens to unused token capacity?
- **EPAM:** would you build on DIAL or on my existing platform, and who maintains it after launch?
- **IBM Consulting:** which parts of the proposal require watsonx, and what is the exit path if I move models later?
- **HatchWorks AI:** for a pod that replaces a team of 8 to 12, who is the accountable lead and how is quality measured?
- **Master of Code Global:** what is the pilot price, and what is the next phase cost if the proof of value succeeds?
- **Tribe AI:** how many forward deployed engineers will join, for how long, and how do you hand over?
- **Loka:** which AWS funding programmes apply to us, and what do we owe if funding is not approved?
- **Ode with Anthropic:** how do you handle a use case where another model is better, and what delivery history can you show?

Typical budget is far below the average AI project. Sources: Clutch AI pricing (Sept 2026), ScienceSoft AI page (Oct 2026), Vrisic typical ranges.

## What US AI development companies charge

Most firms on this list do not publish prices. ScienceSoft publishes $10,000 to $100,000 for chatbots and conversational agents, $50,000 to $150,000 or more for agents with enterprise integrations, and $300,000 to $1,000,000 or more for multi component systems. Clutch’s September 2026 data puts the average AI project at $120,594.55, with the most common budget between $10,000 and $49,999 ([Clutch](https://clutch.co/developers/artificial-intelligence/pricing) ). Notice the gap between that average and the most common budget: a few very large projects pull the average far above what a typical buyer spends. Plan on the common range if your scope is one workflow.

Subscription and embedded models hide their price in a different way. Globant meters tokens; HatchWorks AI sells engineers and pods; neither lists a rate. For those models you should ask for the monthly fee, the capacity it buys and the notice period, then multiply by the months you expect to need them. Our [AI development cost guide](https://vrisic.com/blog/ai-development-cost/) compares these figures in detail.

## Worked example: the same project, three routes

This is an illustrative example, not a quote from any firm. A mid size US distributor wants an agent that reads supplier emails and purchase orders, matches them to its ERP and flags mismatches. We assume 5,000 documents a month, one ERP and a target of 80% handled without human touch.

| Route | How it is bought | What you must supply | Main risk |
| --- | --- | --- | --- |
| Fixed scope project (ScienceSoft, Vrisic) | Written scope and price after discovery. Both publish ranges; the agent with ERP integration sits in ScienceSoft’s $50,000 to $150,000 or more band and Vrisic’s $25,000 to $60,000 integrated band. | ERP access, 200 sample documents, an owner | Scope change after signing |
| Embedded engineers (HatchWorks AI, Toptal) | Monthly engineers or pods; no price published for either in our sources | A technical lead, backlog, review time | Open ended spend, quality depends on your steering |
| Subscription (Globant AI Pods) | Monthly fee for metered capacity; amount not published | Product owner, priorities | Capacity used on other work, unclear unit cost per feature |

The arithmetic that matters is cost per automated document. If the build costs $40,000 and 80% of 5,000 documents a month (4,000) save four minutes each, that is 267 hours saved a month. At $30 an hour loaded cost, the monthly saving is about $8,000, so the build pays back in five months ($40,000 divided by $8,000), before hosting and model usage. A route that costs twice as much takes ten months. Any route that needs a technical lead you do not have should be priced with that hire included.

From long list to signed scope in four steps. Vrisic analysis. Durations are suggestions, not firm quotes.

## How to choose an AI or SI development company

Choosing is easier once you separate three decisions that buyers usually mash together: the delivery model (project, capacity or programme), the platform risk (does the work run in your account or the vendor’s), and the commercial risk (what you owe if the first version disappoints). Decide those three in that order, then compare firms inside the model that fits. A firm that is excellent at programmes can be a poor choice for a $30,000 build, and the reverse is also true.

- Start with one workflow and a number: hours saved, calls answered or invoices processed.
- Ask for a written scope, a test plan and a price before you sign.
- Check who owns the code, prompts, data and model keys on exit.
- Ask how the company defines SI if your buyer uses that word.
- Run a small paid pilot before a large commitment. Our guide to choosing an AI development company expands each step.

## Diligence questions that separate firms

Public pages tell you very little about quality. These questions do.

1. **Show me an evaluation report from a past project.** A serious firm can show structure and pass marks, with client data removed.
2. **Who will be on my project, and for how long?** Ask for names and roles, not a team size.
3. **What does a failed call or hallucinated answer cost me?** The answer reveals guardrail design.
4. **Where is my data stored and which sub processors touch it?** Tribe AI states SOC 2 Type II; ask any firm for the report, not the badge.
5. **What does month 13 cost?** Hosting, model usage, licences, support and change requests.
6. **What can I take with me?** Source code, prompts, evaluation data, infrastructure scripts.

## Mistakes buyers make with lists like this

1. **Treating a list as a ranking.** An alphabetical or buyer type list says nothing about who will do your project best. Paid placement lists make this worse; ours is not paid, but it still cannot judge delivery.
2. **Comparing headline prices across different scopes.** A $5,000 low code workflow and a $50,000 agent with enterprise integrations are different products. Compare cost per automated task instead, as in the worked example.
3. **Believing size equals fit.** A firm with tens of thousands of staff may assign your small project to a junior team. Ask who actually builds it.
4. **Skipping ownership terms.** The most expensive surprises come at exit: code on someone else’s platform, prompts you cannot take, per seat fees that grow.
5. **Skipping the pilot.** Every firm here sells a pilot, proof of concept or discovery phase for a reason. A short paid test on your data is the cheapest way to learn how a team works.
6. **Reading a vendor’s own metrics as proof.** Retention rates, star ratings and case study percentages are the seller’s claims. They can be true and still not apply to your case.

## Red flags

- “We build super intelligence” with no definition or evidence.
- No evaluation results on data like yours.
- Licence fees that grow per user with no cap.
- No clear answer on who hosts your data.
- Awards or retention figures with no named source you can check.
- Pressure to sign a large multi year deal before any working pilot.

## How Vrisic can help

If you want one defined AI system at a fixed price, in your own cloud and owned by you, read [how we work](https://vrisic.com/how-we-work/) or our [AI agent development](https://vrisic.com/services/ai-agent-development/) page, then [book a free scoping call](https://vrisic.com/contact/) . We give one fixed price afterwards. See also our [USA page](https://vrisic.com/locations/usa/) for hosting and compliance notes.

If you would rather test before committing, our [AI Pilot](https://vrisic.com/ai-pilot/) costs $1,500 (£1,200, AED 5,500), takes 10 business days and is fully credited against a build started within 60 days.

## Sources

1. [ScienceSoft: About company](https://www.scnsoft.com/about/company) (ScienceSoft)
2. [ScienceSoft: AI software development](https://www.scnsoft.com/artificial-intelligence/software-development) (ScienceSoft)
3. [Thoughtworks: Enterprise AI services](https://www.thoughtworks.com/en-us/what-we-do/enterprise-ai) (Thoughtworks)
4. [Thoughtworks launches Agent/works, 16 June 2026](https://www.thoughtworks.com/about-us/news/2026/thoughtworks-launches-agent-works) (Thoughtworks)
5. [Apax Partners: Thoughtworks](https://www.apax.com/partnerships/thoughtworks/) (Apax Partners)
6. [Globant introduces AI Pods, 5 June 2025](https://www.globant.com/news/globant-introduces-ai-pods-model) (Globant)
7. [EPAM releases DIAL platform as open source, December 2023](https://www.epam.com/about/newsroom/press-releases/2023/epam-releases-ai-powered-dial-platform-for-open-source-helping-companies-quickly-advance-generative-ai-and-llm-driven-solutions) (EPAM)
8. [IBM Consulting expands AI capabilities, 6 May 2026](https://newsroom.ibm.com/2026-05-06-ibm-consulting-expands-ai-capabilities-to-accelerate-enterprise-transformation) (IBM Newsroom)
9. [HatchWorks AI home page](https://hatchworks.com/) (HatchWorks AI)
10. [Master of Code Global formalizes AI pilot program, May 2026](https://masterofcode.com/blog/master-of-code-global-formalizes-ai-pilot-program/amp) (Master of Code Global)
11. [Master of Code Global: AI agent development services](https://masterofcode.com/ai-agent-development-services) (Master of Code Global)
12. [Tribe AI: Forward Deployed AI Engineer (company description)](https://www.tribe.ai/careers/forward-deployed-ai-engineer) (Tribe AI)
13. [Loka: AWS partnership page](https://loka.com/aws) (Loka)
14. [Ode with Anthropic launch release, 15 July 2026](https://secure.businesswire.com/news/home/20260715205134/en/Anthropic-Blackstone-and-Hellman-Friedman-Introduce-Ode-with-Anthropic-an-Enterprise-AI-Services-Firm) (Business Wire)
15. [Clutch: AI development pricing, updated September 2026](https://clutch.co/developers/artificial-intelligence/pricing) (Clutch)
16. [Inaugurating the Era of Super Intelligence, September 2026](https://www.whitehouse.gov/presidential-actions/2026/09/inaugurating-the-era-of-super-intelligence/) (White House)

All company details were read on the sources above in October 2026. Companies change; confirm before you buy.

## Frequently asked questions

### Who are the top AI development companies in the USA?

Well known options include ScienceSoft, Thoughtworks, Globant, EPAM Systems and IBM Consulting for large programmes, HatchWorks AI, Master of Code Global and Tribe AI for mid market and enterprise agent work, Loka for AWS based teams and Ode with Anthropic for mid size firms using Claude. This is a shortlist grouped by buyer type, not a ranking. The best fit depends on your size, cloud, budget and need for certifications.

### What are the top SI (Super Intelligence) development companies in the USA?

SI is the federal naming for the field commonly called AI. No company in our sources sells a system beyond human ability. The same firms that build AI also serve buyers who use the SI term, so judge them on engineering, evaluation and ownership terms. For federal work, check specifics such as FedRAMP authorisation, which IBM states for its IBM Consulting Advantage platform on AWS GovCloud (US).

### How much do AI development companies in the USA charge?

Few publish prices. ScienceSoft lists $10,000 to $100,000 for chatbots, $50,000 to $150,000 or more for enterprise agents and $300,000 to $1,000,000 or more for multi component systems. Clutch’s September 2026 data shows an average AI project of $120,594.55, but the most common budget is $10,000 to $49,999. Vrisic’s typical range is $8,000 to $150,000 or more, fixed after scoping.

### Is this a ranking?

No. The companies are grouped by buyer type and are not scored, because public pages cannot show delivery quality. Vrisic publishes the page, lists itself separately and states its own limits: a young company, no local offices and no long client list. Treat the list as a place to start, then ask each firm for an evaluation report, ownership terms and references.

### Does the SI order affect which company I should hire?

Only if you sell to a federal buyer who uses the term. Ask whether a vendor can follow the buyer’s definition and which authorisations it holds. For private work, choose on evaluation, price and ownership. Do not pay a premium for the SI label alone; in the sources we checked, firms describe the same agents, models and platforms under both names.

### Should a mid size company pick a large firm or a smaller specialist?

Pick on the shape of the work. One workflow worth $20,000 to $60,000 rarely needs a firm built for enterprise programmes, where rates, process and minimum engagement can outweigh the benefit. A programme across many systems, countries or regulators can justify a larger partner. Whichever you choose, run a short paid pilot and get ownership terms in writing first.

### What should I ask a vendor to prove before signing?

Ask for an evaluation report from a comparable project, named engineers and roles, a data flow diagram with sub processors, a month 13 cost estimate and the clause that assigns code, prompts and evaluation data to you. Request SOC 2 or ISO reports rather than badges. A firm that cannot show structure and pass marks for its testing is selling a demo, not a system.

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