Our starting goal: a core FDE team and the first paid pilots.
Future vision · illustrative AI-generated image
Local cloud → our own data centers → business-specific models → models that support humanoid intelligence
Long-term IT capacity targets1 MW → 100 MW → 1 GW
A trusted connection between business and engineers
A Forward Deployed Engineer (FDE) understands a problem in the customer’s working environment, implements an AI solution and takes responsibility for delivery.
Consulting network
Reach real business problems with consultants who know the sector and the customer. Agree the scope, budget and success criteria together.
Core FDE team
Bring together engineers suited to the work. Build a team that uses its own agents and takes responsibility for the solution and delivery.
Measurable delivery
Compare the starting point with the outcome. Build trust through independent expert review, customer acceptance and transparent costs.
Revenue begins with work delivered.
Paid FDE projects and ongoing support come first. Later, fees from completed marketplace work and optional business memberships. Customer value and platform costs are tracked separately.
Transparency starts with a shared measurement framework.
Starting point and measurement period
Accepted outcome and data source
Human effort, agent and compute costs
Maintenance, limitations and unknowns
Time saved, operational improvement and realized cash impact are reported separately. Promotion uses measured results with permission to share.
Every project builds evidence for the next step
Learn while solving problems, then turn those lessons into tools, team capability and evidence for the next funding round.
01
Core team and first projects
Scoped and budgeted pilots through consulting networks. Initial support helps establish the team and demonstrate its ability to deliver.
Evidence to build: clear responsibilities and customer acceptance.
02
Measure, learn, reuse
Record costs, successes and failed attempts. Build reusable solution components, evaluation examples and simulation cases with permission.
Evidence to build: repeat demand, delivery time and unit cost.
03
Clarify ownership
Agree founder roles, the cap table and decision rights before opening the marketplace. Make the effect of new investment on ownership explicit.
Gate: documented responsibilities, ownership and decision rights.
04
Marketplace and agent community
FDEs use their own agents to discover work and solutions, develop together and contribute to simulation tools. People observe progress and results on the web.
Gate: real demand, suitable FDEs and review capacity.
What the next funding round should show
Which customer problem did the previous support help solve? What did we learn and what can we reuse? Which uncertainty will new capital reduce? Each round should answer these questions with stronger evidence.
Responsibilities and ownership are separate dimensions
Founders
Product, engineering, customer delivery, consulting relationships and day-to-day management. Who takes responsibility for what, and with which commitments?
Shareholders
Capital contributions, equity ownership and defined decision rights. Who holds which shares, and how will new investment affect the structure?
A founder can also be a shareholder. FDE contributions or community membership are not designed to grant equity automatically. Names and ownership percentages have not been decided.
Decisions required before the marketplace
Founder roles and commitments; the cap table; decision and representation rights; intellectual property; departure and any vesting terms; rules for new investment. These are business proposals to be agreed by the parties.
An ambitious vision. Progress through evidence.
First, local cloud services using rented capacity. With sustained demand and operating experience, our own servers in colocation, followed by our own data centers.
Target1 MW
Our first facility
A goal to support local cloud services with our own data center capacity.
Progression gate: Repeat demand, operating capability, energy feasibility and separate funding.
Target100 MW
Regional cloud scale
Cloud and business-specific model capacity across one or more sites.
Progression gate: Evidence from operating earlier facilities and growing contracted demand.
Target1 GW
Long-term AI infrastructure
Infrastructure for business-specific models and models that support humanoid intelligence.
Progression gate: Staged demand, energy, capital and research capability.
Planned aggregate usable IT power, potentially across multiple sites. These are not installed capacities, total grid draw, dates or investment commitments.
Business solutions that prepare us for future models
Permitted cases, domain knowledge and evaluation practices prepare the ground for business-specific models. Longer term, the aim is to contribute to models that support humanoid intelligence.
Customer data does not automatically become training data. Physical action and safe control require additional research, data and validation.
First, back the team that will earn trust.
Build the core team, deliver results on real projects and carry what we learn into the next stage.
A team that delivers together
Start with your domain expertise, a business problem you have solved and how you work with your own agent.
Where do you have implementation and delivery experience?
Which example of your work can be reviewed?
What responsibility and time commitment can you take on?
Write to [email protected] to start a conversation. Downloading a brief does not submit an application.
Today and the roadmap
The local simulation laboratory exists. The FDE platform, marketplace, agent community, cloud service, data centers and our own models are on the roadmap.
Laboratory outputs are illustrative scenarios, not evidence of customer returns, field measurements or real control.
