Investors

Every service business needs a brain

A service business is its people's time and expertise. Today that time is spent hand-carrying data between a hundred or more disconnected tools. Hive is the system of intelligence above that stack — one brain that connects everything, answers anything, and runs the routine work across every team. Services are roughly two-thirds of global GDP, and almost none of it has a brain that connects, understands and runs it.

• Businesses worldwide · World Bank359M
• Of global GDP that is services · World Bank~65%
• With one brain to run it all0

Software sold tools. The prize is the work.

Sequoia calls it Services as Software: the next wave does not sell tools you operate, it sells outcomes that get done for you. The software everyone has fought over is a fraction of the budget that sits with the people doing the work.

• The old prize — software you operate~$1.4T
• The real prize — the work itself~$10T+
• For every $1 on software · Sequoia$6 on the work

And time is decoupling from value. As AI reprices service work from hours to outcomes, the firms that deliver more outcomes per expert set the price everyone else lives by. It is already starting at the top: value-based pricing is cutting legal spend 20–50%, 67% of consulting buyers now demand fixed fees (up from 41% three years ago), and WPP is dropping the billable hour. The break lands in the 2027–28 buying cycle.

Trillions in. Almost nothing back.

Enterprises have poured money into AI and seen little return — because the spend chased flashy front-office demos, not the back-office work where the ROI actually is.

• GenAI pilots with zero P&L impact · MIT NANDA 202595%
• Avg spent per initiative; <30% CEO satisfaction · Gartner 2025$1.9M
• AI projects that never reach production · Gartner85%
• Abandoned AI in 2025, up from 17% · S&P Global42%

And buy beats build: vendor-bought AI succeeds about twice as often as internal builds — 67% versus 33%. The mid-market cannot and will not build this themselves, which is exactly the gap Hive fills: straight to the back office, bought, not built.

It's not the model. It's the missing context.

AI cannot act on what it does not understand, and what a service business needs has never been written down. Workflows are undocumented, decisions live in people's heads, tools do not talk, and exceptions are invisible to any model.

• Enterprises with workflow disruption from siloed data · IBM 202682%
• Organisations with fragmented, not integrated systems · Eptura 202596%
• Companies whose data is not AI-ready · Gartner 202557%

As a16z puts it, citing MIT: data agents need context, not a better model. Hive earns that context by doing the work — which is why it can act where others stall.

Two structural failures, getting worse

The AI boom is shipping more disconnected tools, deepening the very problem it claims to solve. Tools don't talk, and the work is still manual.

• SaaS apps per organisation · BetterCloud106+
• Of the workday lost switching between them~9%
• Wasted on software sprawl, a year$90B
• Of software that is AI-enabled today · Gartner~7%
• Of work hours that are automatable · McKinsey60–70%
• Untapped gen-AI value, yearly · McKinsey$4.4T

And the people who need this most cannot build it: 50–71% of non-adopters blame a lack of expertise, and only 27% of small firms feel confident with AI versus 82% of large ones. They don't need another tool — they need the work done, with their team and their tools, out of the box.

One layer. Every service business on earth.

Built bottoms-up, company by company, attacking the labour line rather than just the software line.

• TAM — the services & labour budget AI can now do$10T+
• SAM — software & automation budget, ~3M services firms$120B
• SOM — US + UK/EU services mid-market$12B
• A category-defining outcome — under 1% of the world on Hive$10B ARR

Artificial General Business Intelligence

The destination is AGBI: the world's most advanced business intelligence, trained not on the internet but on the operational reality of how businesses actually run — drawn from the execution memory only Hive accumulates. Every invoice, approval, exception and renewal across every customer is a training signal, and each new customer makes every other one smarter.

The context becomes the model, and only Hive can train it. The operating brain ships now; the Agent Marketplace follows in 2027; AGBI is the bet for 2028 and beyond. That is the long-term vision we are building toward for the service industries.

Get in touch

If you back the layer that runs the business, we would like to talk. Reach us at investors@get-hive.ai.