---
title: "EGILA"
description: "EGILA (SAP, 2025/26): Software records why teams decided something, so AI agents act on that context"
url: "https://www.sugar-network.org/en/projects/egila-2025-26/"
lang: "en"
---

# EGILA

**Software records why teams decided something, so AI agents act on that context**

_Where AI meets human judgment_

- **Corporate partner:** [SAP](https://www.sugar-network.org/en/network/partners/sap/) (https://sap.com)
- **Cohort:** [2025/26](https://www.sugar-network.org/en/projects/cohort/2025-26/)
- **Theme:** [Work & organisations](https://www.sugar-network.org/en/projects/themes/work-organisations/)
- **Type:** Platform
- **Universities:** [Hasso Plattner Institute](https://www.sugar-network.org/en/network/universities/hpi/)
- **Team:** 4 master students
- **Disciplines:** Computer Science, Data Engineering

## Challenge

Distributed software teams lose shared context across time zones. Decisions made in one place stay invisible elsewhere, dependencies surface too late, and AI coding tools ignore team-specific workflows and constraints.

## What they built

An enterprise AI platform that records why decisions are made, tracks dependencies as they form and captures trade-offs in real time. AI agents use this shared decision knowledge to execute tasks, while a cycle-based workflow keeps humans in strategic control.

## Impact

For SAP as enterprise partner, the concept aims to protect institutional knowledge, cut duplicated work and late-stage blockers, and make AI adoption in development teams more confident.

## Full project text

EGILA is an enterprise AI platform that preserves decision-based knowledge in software development teams. It captures why features were built, tracks dependencies and trade-offs, and enables AI agents to execute work while keeping humans in strategic control.

### Challenge

Distributed development teams struggle with a fundamental collaboration challenge: how do you maintain shared context when team members work across time zones, locations, and schedules? Critical decisions made in one time zone become invisible to others. Dependencies emerge too late. AI coding tools operate without understanding team-specific workflows or constraints. The question, "How might we use AI to enhance collaboration in distributed teams?" demands more than chat tools or task trackers. It requires decision intelligence infrastructure: AI that captures why decisions were made, tracks dependencies as they form, and enables distributed teams to build on each other's expertise rather than duplicate or contradict it.

### Solution

EGILA solves distributed collaboration by coordinating humans and AI agents around shared decision intelligence. The platform records why decisions are made, tracks dependencies as they form, and captures trade-offs in real-time. Team members across any timezone access the same context, eliminating invisible work and contradictory decisions. AI agents leverage this knowledge to automate tasks while maintaining team specific patterns and constraints. EGILA's cycle-based workflow ensures coordination happens when needed, not by calendar habit. The result: distributed teams that build on each other's expertise, AI that works the way your team works, and decision knowledge that compounds rather than evaporates across locations.

### Impact

EGILA delivers immediate efficiency gains and long-term strategic value. For development teams, it eliminates context loss, reduces coordination overhead, and enables seamless collaboration across time zones. AI agents execute work while humans maintain strategic control, accelerating delivery without sacrificing quality. For enterprise sponsors, EGILA protects institutional knowledge assets, reduces costs associated with duplicated work and late-stage blockers, and enables confident AI adoption. The platform creates measurable impact: faster time-to-market, improved team productivity, lower turnover costs, and development practices that scale intelligently. EGILA transforms distributed software development from an operational challenge into a source of sustainable competitive advantage.

## Who built it.

- Sara Grau I Bladé, M.Sc. Data Engineering (Hasso Plattner Institute)
- Sriram Mandalika, M.Sc. Computer Science (Hasso Plattner Institute)
- Dwayne Nigel Vaz, M.Sc. Computer Science (Hasso Plattner Institute)
- Parisa Shahabinejad, M.Sc. Computer Science (Hasso Plattner Institute)

## Video

- Team SAP - EGILA by HPI d-school - EXPO Teasers 2026: https://www.youtube.com/watch?v=3IlpJ57WOQc

## Sources

Summarised by the SUGAR editorial team from the team’s project page.

Open the 2025/26 booklet: https://drive.google.com/file/d/1YuEdSu72p4SvYlsdPbHL04C_lRETW8r1/view?usp=sharing