How Event Agency El Padre Accelerated Proposal Creation by Up to 50% with AI

How Event Agency El Padre Accelerated Proposal Creation by Up to 50% with AI

In the competitive world of events, where every minute counts, event agency El Padre had to face a challenge that many companies in the industry deal with: how to increase the number of proposals submitted without sacrificing their high quality? The answer turned out to be deploying the AION platform with advanced AI support. The results? 10-50% faster proposal preparation, 10-15% higher production department productivity, and 25-30 people supported by AI in their daily work.

In this case study, I'll walk you through step by step how we carried out the implementation and what concrete business benefits this solution delivered.

The Business Problem: When Quality Meets Time Pressure

El Padre is a renowned event agency that prepares comprehensive proposals for its clients -- from creative concepts through visualizations to detailed cost estimates and schedules. Every proposal is a custom project requiring involvement from two key departments:

Time Is Money -- Literally

Before deploying AION, preparing a single proposal took:

• Creative department: 6-10 hours (research, concept, visualizations)
• Production department: 4-6 hours (pricing, cost estimation, logistics)
• Total: up to 16 hours per proposal

For smaller projects (50-100K PLN), this workload was unprofitable -- but without a professional proposal, winning the bid was nearly impossible.

Key Challenges

1. Overloaded creative team -- too many projects, too little time for each
2. Time-consuming creative and production work -- manual cost estimation, searching through previous proposals, creating visualizations
3. No knowledge centralization -- meeting transcripts, cost estimates, and archived proposals were scattered across various OneDrive folders
4. Disproportionate proposal preparation cost -- especially for smaller projects where the margin didn't justify the effort

The agency faced a dilemma: either grow the team (which generates costs) or find a way to speed up processes without sacrificing quality.

The Solution: AION as the Central Hub for Proposal Processes

We decided to deploy the AION platform -- a system for managing AI-supported processes. The key to success wasn't just introducing AI tools, but above all integrating and centralizing data and adapting the workflow to the team's real needs.

Technology Stack

• AION -- platform for managing AI-supported processes
• OneDrive -- integration with existing file system (automatic synchronization)
• AI transcription tools -- automatic recording and processing of meetings
• AI assistants -- targeted support for specific proposal stages
• Knowledge base search system -- quickly finding information from previous projects

Implementation: How We Did It in 6 Weeks

We split the implementation into three main phases, completed over approximately 6 weeks:

Step 1: Data Integration and Centralization (Weeks 1-2)

The first step was organizing the information chaos. We automated file synchronization from OneDrive to the AION platform, creating one central place for:

• Client meeting transcripts -- every conversation automatically recorded and processed
• Knowledge about all projects -- collaboration history, preferences, notes
• Cost estimates and pricing -- price database and calculation templates
• Archived proposals -- as a pattern base and reference points for new projects

This gave the team instant access to all organizational knowledge -- without searching through dozens of folders.

Step 2: Deploying Intelligent Tools (Weeks 3-4)

In the second phase, we launched AI tools to support specific tasks:

• Automatic meeting recording and transcription -- every client meeting was recorded (with consent) and then processed into a transcript and structured data
• Processing transcripts into structured data -- AI extracted key information: budget, preferences, requirements, deadlines
• Visualization generator -- AI helped quickly create initial visual concepts for event proposals
• Knowledge base search system -- ability to filter by meetings, projects, clients, and quickly find similar cases

Step 3: Workflow Implementation and Support (Weeks 5-6)

The final phase was adapting the system to daily work and training the team:

• Preparing targeted AI assistants -- each stage of the proposal process (research, concept, pricing, finalization) received a dedicated AI assistant
• Technical support during implementation -- daily standups, resolving issues in real time
• Team training -- 25-30 people went through workshops and onboarding with AION
• Pilot tests and optimization -- fine-tuning the workflow based on team feedback

Results: The Numbers Speak for Themselves

After 6 weeks of implementation, El Padre started seeing the first effects, which only grew over time:

Key Metrics

• 10-50% faster proposal preparation -- depending on project complexity (simple proposals up to 50% faster, complex ones ~10-20%)
• 10-15% higher production department productivity -- thanks to automated pricing and cost estimation
• 25-30 people supported by AI -- practically the entire team uses AION in their daily work
• Dramatic increase in monthly proposals submitted -- without growing the team

ROI: Time Savings

The numbers are impressive:

• Average 5-8 hours saved per proposal
• At 15 proposals per month = 75-120 hours saved
• That's the equivalent of 2-3 full-time employees

Business Benefits

Efficiency gains:

• The production department can handle more projects without additional hires
• The creative team has more time for innovative concepts
• Ability to bid on smaller projects (previously unprofitable)

Quality and consistency:

• All proposals maintain a high standard thanks to knowledge base access
• Lower risk of pricing errors (automated cost estimation)
• Faster access to archived projects as templates

Brand image and competitiveness:

• Strengthened image as an innovative, modern agency
• Faster response time to proposal requests (competitive advantage)
• Ability to serve more clients

Additional benefits:

• Knowledge centralization -- easier onboarding for new employees
• Better project documentation -- everything in one place
• Scalability -- the solution grows with the company

Client's Voice: What Does El Padre Say?

"The AION deployment significantly simplified and accelerated our event proposal preparation process in many aspects. We appreciate the flexibility of the solution and the support of the implementation team. Every day we discover new applications for AION in our organization and take full advantage of its capabilities, even though we're only using a fraction of its potential."

Jakub Cwiklinski Vice President at El Padre

That last point is particularly interesting -- the El Padre team is using "just a fraction of the potential" of AION, which means benefits will continue to grow over time as they discover new applications for the platform.

Key Takeaways: What Can You Learn from This Case Study?

1. AI in the Event Industry Is the Present, Not the Future

El Padre shows that you can achieve up to 50% process acceleration -- and in an industry that seems highly creative and difficult to automate.

2. Data Integration and Centralization Is Key

Without a unified knowledge base, AI has nothing to draw from. The first step -- organizing data -- was the foundation of success.

3. Implementation Doesn't Have to Be Long

6 weeks was enough for 25-30 people to work more efficiently. You don't need months-long transformation projects.

4. ROI Is Measurable

Time savings (75-120h monthly) translate directly into the ability to serve more clients without increasing costs.

5. AI Supports, It Doesn't Replace

The creative team still creates unique concepts -- AI simply relieves them of tedious, repetitive tasks.

Who Is This Solution For?

AI implementation in proposal processes works particularly well for:

• Creative and event agencies with a high volume of proposals
• Companies where the proposal process is complex and time-consuming
• Organizations looking to scale without proportionally growing their team
• Businesses seeking a competitive edge through speed and innovation

If your company faces similar challenges -- overloaded teams, time-consuming processes, lack of knowledge centralization -- it's worth considering AI deployment.

FAQ

What results can you achieve by automating the proposal process with AI?

Typical results include 10-50% faster proposal preparation, 10-15% team productivity increase, and 75-120 hours saved monthly with 15 proposals. This allows you to serve more clients without growing the team and bid on smaller projects that were previously unprofitable.

How long does it take to implement AI in the proposal process?

A typical implementation takes about 6 weeks in three phases: data integration and centralization (weeks 1-2), AI tool deployment (weeks 3-4), workflow implementation and team training (weeks 5-6). You don't need months-long transformation projects to see the first results.

How does AI support proposal creation in creative and event agencies?

Automatic meeting transcription and extraction of key information (budget, requirements, deadlines), searching archived proposals as templates, automating cost estimates and pricing, and generating initial visualizations. AI handles the tedious tasks so the creative team can focus on unique concepts.

How do you calculate ROI from proposal process automation?

Measure average proposal preparation time before and after implementation, multiply the savings by the number of proposals per month and the team's hourly rate. Example: 5-8h savings x 15 proposals = 75-120h/month. Those hours can go toward more proposals or creative projects at no additional cost.

What types of companies benefit most from AI-powered proposal automation?

Creative and event agencies with a high volume of proposals, companies with complex and time-consuming proposal processes, and organizations looking to scale without proportionally growing their team. Key qualifying signals: overloaded teams, knowledge scattered across folders, and smaller projects that aren't worth the effort.