The Efficiency Engine: How Fora Built an AI-Native Operating System to Scale Post-Series C
90%+ reduction in analytical cycle times & widespread operational adoption
Quick Overview
- Client
- Fora
- Industry
- Travel & Tech
- Challenge
- Following a $60M Series C fundraise, Fora faced a critical mandate: Scale revenue without scaling headcount. This required re-architecting core workflows across Data Science, Marketing, Operations, and Executive Leadership.
- Solution
- GSD at Work deployed a high-intensity transformation program centered on mining "Digital Exhaust"—feeding unstructured data (Slack logs, Intercom tickets, email threads, meeting transcripts) into secure, reasoning-capable AI environments to diagnose bottlenecks and build solutions in real-time through Action Workshops.
- Date
- May 2025 - November 2025
Key Results
- Data Science Velocity: Complex hypothesis testing reduced from 3–4 days to ~1 hour
- Operational Clarity: Analyzed 90 days of internal communication to restructure decision-making frameworks
- Adoption at Scale: 46% "immediate lightbulb moments" across entire company during single-day rollout
- Commercial Impact: Created replicable workflow to turn client email history into marketing assets in minutes
Executive Summary
Following a $60M Series C fundraise, Fora faced a critical mandate: Scale revenue without scaling headcount.
To achieve this, Fora CEO Evan Frank and Head of People Operations Georgia Flaum partnered with GSD at Work for a high-intensity transformation program. Moving beyond basic tooling, the engagement re-architected core workflows across Data Science, Marketing, Operations, and Executive Leadership.
The Highlights
- Data Science Velocity: Complex hypothesis testing reduced from 3–4 days to ~1 hour.
- Operational Clarity: Analyzed 90 days of internal communication to restructure, design, and implement decision-making frameworks.
- Adoption at Scale: Achieved 46% “immediate lightbulb moments” across the entire company during a single-day rollout, catalyzed by a company-wide competitive hackathon.
- Commercial Impact: Created a replicable workflow to turn client email history into marketing assets in minutes.
The Digital Exhaust Engine: Fora's AI transformation methodology
The Methodology: Mining “Digital Exhaust”
The core thesis of the engagement was that the answers to Fora's efficiency problems were already hiding in their data—their “Digital Exhaust.”
By feeding unstructured data (Slack logs, Intercom tickets, email threads, and meeting transcripts) into secure, reasoning-capable AI environments (Claude Code, OpenAI Codex, Google AI Studio), we could diagnose bottlenecks and build solutions in real-time. We executed this through Action Workshops: live, time-boxed sessions where real work was completed, not just discussed.
Deep Dive: Departmental Transformations
1. Data & Analytics: Compressing Time-to-Insight by 95%
The Challenge: The Data team was bogged down by ad-hoc requests. They needed to validate a complex strategic hypothesis. Traditionally, this required days of SQL queries, data cleaning, and dashboard construction.
The AI Intervention: We deployed Claude Code and Codex (autonomous coding agents) in a multi-agent workflow.
- Step 1: Ingested raw CSVs of historical data.
- Step 2: Ran parallel analysis streams using different AI models to cross-verify results.
- Step 3: Calculated key statistics to scientifically map trends over time.
The Outcome: The AI helped the team go from hunches to confirmation of a structural reality regarding core platform use that allowed leadership to prioritize strategic initiatives immediately.
“If I had to sit manually and do that, it would have taken me probably three or four days... [with this workflow] it was down to like an hour.”
2. Operations: Taming the “Slack Chaos”
The Challenge: As the team grew to ~150 employees, decision-making slowed. Channels were flooded with notifications, and it was unclear who owned final decisions.
The AI Intervention: We performed a massive export of 90 days of Slack history from high-traffic channels. We fed this unstructured text into a long-context AI model to diagnose communication patterns.
The Outcome: The AI identified that nearly 30% of messages were circular consensus-seeking rather than decision-making. It worked with leadership to “co-create,” define, and come up with a precise rollout plan for a new operational framework: DDF (Decider, Doer, FYI).
- Implementation: Fora rolled this framework out to a pilot channel.
- Result: Reduced thread count, faster resolution times, and a codified “Area of Responsibility” map for the org.
Before & After: The DDF framework transformed decision-making at Fora
3. Advisor Marketing: The “Story-to-Sales” Pipeline
The Challenge: Fora leadership wanted to make it easier for advisors to spend more of their time doing what they're best at. Given the high value and rich stories, or “micro-cases,” contained their complex work (e.g., “Planning a multi-stop Nordic graduation trip for 7 people”), there was an emerging opportunity to transform those data into marketing assets that attract new business, and much faster than it would normally take.
The AI Intervention: We ran a live “lab” with an advisor. We used MailMeteor to export her raw email correspondence regarding a complex trip, sanitized it, and fed it into a Custom GPT.
The Outcome: In under 20 minutes, the AI transformed a messy email thread into:
- A compelling narrative case study.
- A structured Instagram Carousel caption.
- A visual storyboard for creative assets.
The Story-to-Sales Pipeline: Email threads become marketing assets in under 20 minutes
Scalability: This workflow was converted into content for a proposed training module, with the goal of allowing any advisor to turn their inbox history into high-quality marketing content without staring at a blank page.
4. Executive Proficiency: The “B+ Gate”
The Challenge: VP needed to improve the quality of her team's memos and decks but lacked the time to provide detailed coaching on every draft.
The AI Intervention: We built a Custom GPT trained specifically on the VP's “Gold Standard” examples, rubrics, and communication style.
The Outcome: We established a new protocol: Team members run their drafts through the “Manager Bot” first. If the AI grades it below a “B+,” they iterate. The VP only reviews work that has already cleared the AI quality gate.
Result: Higher quality first drafts reaching the executive level and a continuous feedback loop for junior staff.
The Cultural Pivot: The “Test Kitchen” Offsite
To ensure these wins weren't isolated to leadership, we launched a company-wide activation.
1. The Vapi Hotline (Voice AI)
Prior to the offsite, we set up an AI voice agent that interviewed 100+ employees about their bottlenecks.
- Data Gathered: 87 completed interviews generating 10+ hours of transcripts.
- Insight: We used this data to build a heat map of where employees felt “energy drain” vs. “energy gain.”
2. The Live Build
On stage, we took the “burning questions” sourced from the hotline and created, in real-time, an end-to-end AI-powered prototyping process, which included a custom voice assistant for asynchronous user interviews, a landing page for a new product idea, and a 24-second video advertisement to communicate the core value proposition and experience to prospective users.
3. The Results
- 46% of employees reported a “lightbulb moment” regarding AI utility immediately following the session.
- Cross-functional teams built working prototypes (using Lovable) in a single afternoon—including a client tracking tool that would have previously required engineering resources.
The Legacy: Institutionalizing Innovation
The engagement concluded not just with new tools, but with a new organizational infrastructure designed to sustain velocity.
- The “WisprFlow” Standard: Dictation tools were rolled out company-wide to increase communication throughput and reduce AI iteration cycle times.
- The Community of Practice: A dedicated internal channel was established for employees to share prompts, wins, and new workflows.
Client Feedback
“I think there's been a massive evolution in the AI culture at Fora from June until now... Having you as a resource who deeply understands the market and has business experience was just really great. From an investment perspective, it's a 5/5.”