Private briefing for SP Digital
See how we would take one SP workflow from evidence to production, with proposed use cases, a reference architecture, and a clear delivery plan. Enter your business email to access the briefing.
Prepared for SP Digital and SP Group. Not for wider distribution.
AI agents accelerate the build. Senior engineers govern every gate. You get AI‑native speed and German engineering standards. Full ownership, from end to end.
More than 15 years building engineering organizations for mission-critical systems.
More than 30 years in intelligent transport and traffic engineering, including leadership roles at Siemens.
Leads software architecture for mission-critical infrastructure projects.
A hands-on solution architect across Eastgate’s most critical engagements.
Leads Eastgate’s global growth and strategic partnerships.
DAP is SP’s data and AI platform. Any connected system must meet the CII cybersecurity code, while SP’s public position on AI sovereignty points to a clear need for control over data and infrastructure.
SP is developing its own AI and agent capabilities. However, we found no public standard for runtime controls, approval steps, or workflow orchestration. Without those foundations, a successful pilot still has no clear route into daily operations.
Asset management, customer service, sustainability, corporate productivity, and engineering delivery all rely on DAP. Each area brings different systems, definitions, permissions, and operating requirements.
SP’s 15 MW virtual power plant pilot operates within EMA’s two-year sandbox. That requires a clear record of delivery and compliance evidence. Public information does not show how much of this work is automated today.
The services below cover the path from software delivery and operational data to governed agents and private AI infrastructure. SP can start with the part the selected workflow needs.
Build and modernize software faster while senior engineers remain accountable for quality, security, and release.
Turn operational data into decisions that people can understand, verify, and act on.
Connect company knowledge, agent workflows, human approvals, and system updates through one governed platform.
Keep sensitive data, models, and workflows within SP-controlled infrastructure, whether on-premises, in a private cloud, or air-gapped.
Our Agent‑Centric Development Cycle gives AI agents defined tasks, clear boundaries, and evidence to produce. Senior engineers set the standard, review the result, and approve every release.
Enterprise AI OS connects the information SP already holds with the workflows its teams already follow. Agents gather the relevant context, prepare a recommendation, request approval, and make only the system updates they are permitted to make.
The intelligence layer can support a wider agentic transformation or work with a platform SP already operates.
Information from different sources enters one shared context while keeping its existing permissions and access rules.
Agents and people follow the same sequence of tasks, reviews, approvals, and system updates.
Policies, permissions, approval rules, and evaluation checks govern each step. The platform records what happened and why.
Once the responsible owner approves a decision, the workflow makes the permitted system update and records the result.
The architecture starts with SP’s existing systems and builds towards the tools its teams use. Each layer shows SP’s likely role, where Eastgate could contribute, and what discovery still needs to confirm.
Supported program areas
We first agree on the outcome, baseline, and delivery boundaries. SP can then choose the team structure that matches the scope and level of ownership required.
A long-term engineering team that grows with SP’s roadmap. Eastgate manages delivery and keeps responsibilities clear as the work expands.
A defined scope delivered against agreed milestones and acceptance criteria.
An onsite solution and domain lead works with SP’s owners, supported by Eastgate’s offshore engineering team. The pod takes one use case from discovery into production.
SP works with operational data, long-lived infrastructure, and systems that require strict release control. Eastgate engineers already work in these environments.
More than 12 years of engineering work with Siemens Mobility and Yunex Traffic.
Mission-critical airport automation delivered for Siemens Logistics.
Production experience across energy trading, sensor-based maintenance, edge AI, SCADA-adjacent systems, and programmable logic controllers.
These projects span different industries, but each required software that remained dependable, traceable, and usable under real operating conditions.
Engineers search thousands of technical documents. Every answer uses only information the person may access and includes the original source.
Relevance to SP: permission-aware answers over private technical knowledge.
A production platform processes live energy data and supports market decisions under strict latency requirements.
Relevance to SP: real-time energy data and market systems integrated and tested together.
Real-time control software connects with Siemens programmable logic controller systems inside a safety-critical operation.
Relevance to SP: software working across enterprise and operational technology boundaries.
The system turns vibration and load data into asset-risk flags for people to review before taking action.
Relevance to SP: sensor data converted into reviewable maintenance decisions.
AI models run on edge graphics processing units and trigger a programmable logic controller reject when the system detects a fault.
Relevance to SP: real-time AI operating at the boundary between enterprise software and operational equipment.
Move from a successful pilot to reliable operations without rebuilding the system from scratch.
Five reasons prototypes stall and what teams can do about them.
See how specifications, harness engineering, automated checks, and human approval work together.
Learn why AI-assisted modernisation still needs clear requirements, system knowledge, and release controls.
These public developments explain why the proposed workflows may matter now. We have treated them as context rather than confirmed requirements.
The pilot combines up to 15 MW of SP-owned solar, battery, and EV-charging capacity within EMA's two-year sandbox.
SP Group EMAThe announced scope covers design, integration, testing, and scaling. Public information does not define responsibility for forecasting, bidding, or settlement.
UniversSystems connected to critical infrastructure, including their AI components, remain under the asset owner’s oversight.
Cyber Security Agency of SingaporeSP’s VPP was named the 2026 Smart Grid winner. The award recognises the programme but does not measure its operational performance.
Enlit AsiaSP’s data science leadership joined a regional discussion about AI sovereignty in the Asia-Pacific region.
SP is a sponsor, with its Group CEO among the announced speakers.
A working session will identify the workflow, platform fit, and data foundation worth starting with. Bring the workflow owner and current baseline. We will bring the engineers and map a practical route to production.
“Eastgate has been a long-term strategic partner for our ITS division. Their reliability and quality of deliveries have been exceptional.”Michael GärtnerVP, Siemens Mobility ITS US