Very Big Things - AI/ML Development

Award counts are the easiest credential to accumulate and the hardest to interpret. Very Big Things reports over a hundred and forty international awards alongside eight verified client reviews, and the gap between those two numbers is the most useful thing to understand before engaging.

What They Actually Do

The firm works with startups and enterprises across several sectors.

Engagements combine strategy, design, and engineering in one team.

Work covers both new products and rebuilt existing systems.

The firm sells transformation programmes rather than discrete projects.

The firm provides AI consulting and builds digital products, with strategy, design, and engineering delivered together. Documented work includes generative AI consulting for a travel business alongside a website redesign and booking engine integrations, and a proof of concept converting vector imagery into production-ready files.

Current positioning centres on workflow redesign, platform modernisation, and a named framework the firm deploys alongside client systems.

Services on Offer

• Generative AI consulting — Identifying and implementing AI uses, the stated current focus.
• Product design and engineering — Digital products for startups and enterprises.
• Workflow transformation — Rebuilding manual or fragmented business processes.
• Platform modernisation — Updating legacy systems alongside AI adoption.
• Proprietary framework — A named foundation deployed alongside existing systems.
• Branding and design — Creative work alongside technical delivery.
• Ongoing support — Maintenance after implementation.

Where They Fit Best

Buyers needing adoption support alongside build fit the stated approach.

Companies modernising legacy platforms alongside AI adoption fit the current focus.

Buyers wanting strategy and delivery from one supplier fit the stated model.

Organisations rebuilding a core workflow rather than adding features fit the positioning.

Enterprises and funded companies pursuing AI adoption fit the stated positioning. Named clients include cruise, telecommunications, logistics, and fitness brands.

No minimum project size or hourly rate is published, which suggests engagements are scoped individually rather than packaged.

Tradeoffs Worth Knowing

The firm has rebranded its positioning more than once. Read current material rather than older descriptions.

Documented review activity is recent rather than accumulated over years.

Undisclosed pricing suits large engagements and frustrates smaller buyers. Establish budget fit in the first conversation.

The verified review base is small at eight entries against a very large award count and an impressive client roster. Awards reflect submission effort and craft recognition rather than delivery reliability, so weight the client accounts more heavily.

No pricing information is published at all, which makes budget fit impossible to assess before a conversation.

The firm has repositioned substantially over time, from digital product agency to AI transformation partner. Read recent references rather than older material.

Branded framework names appear throughout the marketing. Proprietary labels are constructs, and what matters is whether the underlying practice survives reference checks.

The similar name to another firm in this directory complicates research. Confirm which company you are reading about.

Practical Notes

Ask for references from projects completed within the past year.

Confirm what a first engagement typically costs.

Ask how the firm measures return on AI implementations.

Confirm which staff sit domestically and which elsewhere.

Check ongoing costs once AI systems reach production.

The firm operates from Florida with a development presence in eastern Europe.

Documented outcomes include annual value figures cited in company case studies.

Award categories cited span technical achievement, product innovation, and experience design.

One client describes a consultative approach reviewing their current AI use before recommending changes.

Another praises the ability to listen and then implement current technology.

Communication runs through virtual meetings, email, and messaging platforms.

Ask for pricing indications early, since nothing is published.

Request references from recent AI engagements specifically.

Confirm what the proprietary framework actually involves.

Ask about the scope of named enterprise relationships.

Ask which senior people stay involved after strategy.

Confirm testing scope within the quoted price.

Agree acceptance criteria for each milestone.

Check data handling for AI training material.

How They Compare

Bringing strategy, design, and engineering under one team addresses a real problem, since split responsibility is where transformation programmes usually fail.

The award record is genuine and reflects craft recognition rather than delivery reliability. Both matter and they measure different things.

Named clients span several large consumer and technology brands, though engagement scope is unstated.

Against large consultancies, this brings design craft alongside strategy. Against pure engineering firms, the consulting layer is the differentiator. Against smaller AI specialists, the award record signals craft while the review base is thin. For an enterprise pursuing AI adoption with budget to match, the positioning is coherent.

What to Verify Before Choosing Very Big Things

• Pricing indications, since nothing is published
• References from recent AI engagements
• What the proprietary framework involves
• Scope of named enterprise relationships
• That you have the right company, given the name overlap
• Ongoing costs after AI systems go live
• Ownership of models, prompts, and code
• Team composition assigned to your programme
• Timeline commitments and slippage terms
• Support arrangements after delivery