Automating Context and Confidence

Delivering complex digital commerce programs on a fixed-cost, fixed-scope basis demands a precise understanding of context. Each project involves hundreds of moving parts, from sales discovery notes and interview transcripts to Jira tasks and design files.

Historically, teams relied on manual document uploads, one-off Slack messages, and static spreadsheets to bridge the transition from sales to delivery. For years, this fragmented flow of information created several challenges:

Onboarding friction

Project leads often spent days collecting, reviewing, and synthesizing the latest data from sales, strategy, and delivery teams.

Requirements Consistency

Without a unified source of truth, early project documentation varied in completeness and could contain conflicting information as decisions shifted over time.

Hidden risks

Key dependencies or scope shifts could go unnoticed until late in delivery.

Relying on manual effort to overcome these issues left less time for Orium's teams to focus on higher-value work and client outcomes. The organization needed a system that could unify context automatically—reducing overhead while ensuring every fixed-cost engagement began with the same clarity and confidence.

The idea for Genie took shape from a simple realization: if Orium could automate the repetitive setup work that happens at the start of every engagement, teams could focus more time on higher-value problem solving and client strategy. With that goal in mind, designers and delivery leads began experimenting with lightweight automations and early custom GPTs to summarize project material and answer contextual questions.

As those prototypes matured, the team saw a bigger opportunity. A "supervisor" agent—if given access to live data—could go beyond summarizing information to orchestrating delivery itself through many specialist sub-agents. That insight transformed the concept from static knowledge storage into a dynamic, agentic system capable of ingesting live project data, interpreting it, and triggering automated workflows.

With the vision in place, the team began developing Genie as the backbone of a new delivery approach—one that embeds intelligence directly into Orium's operations to drive consistency, speed, and confidence across every project.

Genie functions as an agentic context engine and automation layer that connects directly to Orium's live project ecosystem. Built on n8n—selected for its ability to connect to live data sources when other tools could only handle static uploads—the system was architected to:

• Synchronize automatically with Orium's operational systems (Jira, Slack, Mavenlink, and internal databases).
• Maintain persistent awareness of project context and state.
• Deliver actionable insights directly into daily workflows without requiring manual intervention.

Rather than existing as a standalone AI project, Genie was embedded into the fabric of delivery, becoming the foundation of Orium's broader agent and agent-infrastructure initiative. Every capability was designed to minimize human handoffs, reduce redundancy, and ensure every contributor works from the same live, validated context. Genie takes care of the repetitive setup and documentation work, giving project leads more space for the real decision-making and client-facing judgment work.

Key capabilities include:

• Contextual awareness: Consolidates project data from multiple systems, allowing teams to query or summarize the most current information in natural language.
• Automated requirements and backlog generation: Draws from Orium's proprietary requirements database and historical project insights to create structured, traceable backlogs aligned with scope and industry context.
• Risk identification and reporting: Surfaces emerging risks and generates daily digests and weekly executive summaries, providing visibility across every phase of delivery.
• Documentation automation: Produces presentation decks, interview guides, and executive summaries by analyzing sales transcripts, design notes, and delivery updates.
• Workflow support: Monitors time tracking, sends automated reminders, and aligns delivery cadence with planned scope and hours.

Genie also raises the bar for transparency and safeguards. It double-checks the information it works with, following Orium's privacy best practices, and stays within approved project context. Every output includes clear source citations and a complete audit trail, and the system avoids fabricating content, so teams can trust that each insight is grounded in real project data and handled responsibly.

Since its introduction, Genie has fundamentally improved Orium's ability to deliver consistent outcomes under fixed-cost, fixed-scope engagements. Key outcomes include:

• Full adoption: 100% adoption rate across all new client-facing projects since launch.
• Faster onboarding: Up to 75% reduction in average team onboarding time, measured by time-to-first-productive-task for new team members.
• Consistent backlog quality: 98% of generated requirements accepted on first review by Project Leads.
• Automated reporting: 100% of projects now deliver weekly, automated executive summary decks, reducing manual reporting time by over 50%
• Improved cross-project consistency: 60% decrease in requirements gaps and clarification requests during handoff between teams.
• Reduced project risk: 85% of fixed-cost, fixed-scope projects report fewer risk-related escalations due to improved requirement clarity.
• Increased stakeholder confidence: Higher NPS and feedback scores from project leaders, reflecting greater confidence in project readiness.

Looking ahead, Genie's architecture is built to scale. Planned expansions include deeper system integrations to support pre-sales estimation and discovery, predictive analytics to simulate delivery risk, and secure collaboration features that let clients track progress and insights alongside Orium's teams. And throughout that evolution, Genie is designed to empower our people, not replace them. It keeps recommendations grounded in transparent project data, and ongoing team feedback will guide how it grows, from sharper risk modeling to richer pre-sales context.

Through these advancements, Genie is moving from an internal tool to a core platform capability, an adaptive system that strengthens Orium's fixed-cost, fixed-scope model and amplifies the expertise of every team involved.