The democratization of AI through low-code automation platforms isn't just changing how work gets done — it's transforming who can participate in the AI revolution. By empowering teams to build their own intelligent workflows, we've unlocked efficiency at a scale that would have been impossible with a centralized AI development approach.
Shawn LimStaff Engineer @ Funding Societies
This is the story of how Southeast Asia's largest SME digital finance platform proved that AI isn't just for engineers — it's for everyone. What began as a search for efficiency evolved into a platform for innovation, democratizing AI across Product, Sales, Credit, Collection, Client Experience, Operations, Finance, and Marketing.
Funding Societies faced a common enterprise challenge: how to scale AI and automation adoption beyond the engineering team while maintaining the security and compliance standards required in financial services. Their traditional approach — building custom AI systems with dedicated engineers — created bottlenecks.
The solution? An internal champion program, a self-hosted enterprise platform, and a commitment to putting automation tools in the hands of every team. The result is 100+ workflows running in production, saving nearly a quarter of a year in collective manual task hours.
The Company
Funding Societies | Modalku is the largest SME digital finance platform in Southeast Asia, providing business financing and payment solutions across Singapore, Indonesia, Thailand, Malaysia, and Vietnam. They've built critical financial infrastructure for a region where small businesses often struggle to access traditional banking services.
The company's growth speaks to their impact: backed by Sequoia India (Peak XV), Softbank Vision Fund, Khazanah, and SMBC Bank, they serve thousands of small and medium enterprises with innovative financial products that traditional banks often won't offer.
Operating across five countries in a heavily regulated industry means compliance isn't optional — it's foundational. Every technology decision must account for data sovereignty, regulatory requirements, and security standards that would make most automation platforms non-starters.
When Funding Societies proved AI's value with their first loan application chatbot, they saw the potential. But extending those benefits to streamline the hundreds of internal back-office workflows inherent to financial services required a fundamentally different approach.
The Challenge
As a regulated fintech company operating across five countries, Funding Societies faced a common enterprise challenge: how to scale AI and automation adoption beyond the engineering team while maintaining the security and compliance standards required in financial services.
Their traditional approach — building custom AI systems with dedicated engineers — created bottlenecks. While they had proven AI's value with their first loan application chatbot, extending these benefits to streamline the hundreds of internal back-office workflows inherent to financial services required a different approach.
How do you democratize AI across an entire organization — without compromising the security, compliance, and governance that financial services demand?
- 01Regulatory compliance — Operating in financial services across five countries means stringent data handling requirements. Self-hosted deployment wasn't a preference — it was a requirement.
- 02Technical depth for developers — The platform needed to support complex integrations and custom pieces for proprietary systems, not just simple out-of-the-box connectors.
- 03Accessibility for business users — If only engineers could build automations, they'd never scale. Marketing, Operations, Credit, Sales — every department needed to participate.
- 04Strong AI integrations — Native integration with cutting-edge language models was essential for document processing, intelligent triage, and content generation at scale.
- 05Open source transparency — For security auditing and the ability to contribute back, they needed full visibility into the platform's codebase.
The Solution
Funding Societies selected Activepieces as their automation platform, deployed as a self-hosted enterprise instance to meet regulatory requirements. The platform's combination of technical depth for developers and accessibility for business users made it ideal for their democratization goals.
The Champion Model
Rather than relying solely on external training, Funding Societies developed an innovative internal champion program:
- 1Each department identifies a technical champion
- 2Champions complete Activepieces bootcamp training
- 3Champions receive three dedicated sessions with the internal automation team
- 4Champions then build automations and train their own teams
"The previous approach had someone external teaching the basics. This time we wanted it driven internally, because we noticed one issue — it was really difficult during support sessions because someone from outside wouldn't have a lot of the internal context of the company."
— Shawn Lim, Staff Engineer
Why Activepieces Won
| Requirement | How Activepieces Delivered |
|---|---|
| Technical flexibility | Developers can build complex integrations and custom pieces |
| Business user friendly | Low-code interface approachable for non-technical teams |
| Compliance ready | Self-hosted deployment meets stringent financial services requirements |
| Strong AI integrations | Native integration with cutting-edge language models |
| Open source | Transparency, security auditing, and contribution capability |
Technical Implementation
- Self-hosted enterprise instance
- Internal champions manage upgrades
- Custom pieces for proprietary integrations
What They Built
AI-Driven Document Review for Payments
The problem: Payment-related documents required manual validation — checking invoice structures, verifying official logos, matching data against expected payment records. With the transaction volume Funding Societies processes, this consumed thousands of hours annually.
The solution: An intelligent document review system combining OCR and LLM technologies. The workflow triggers when a new payment is created, extracts key data using OCR, validates authenticity (official logos, invoice structures), performs fuzzy matching against expected payment data, and provides real-time feedback with manual fallback for edge cases.
The impact: Eliminated thousands of manual review hours yearly. The system scales naturally with transaction volume, enabling exponential growth without proportionally increasing headcount.
Intelligent Support Triage with RAG
The problem: Production support requests needed intelligent routing. Manual triage created delays, inconsistent assignments, and required engineers to be available around the clock — including holidays.
The solution: A Retrieval-Augmented Generation system that automatically routes support requests. All past production support requests are stored in a vector database. When new requests arrive, the system analyzes them, compares to historical patterns, and routes to the optimal squad based on expertise and resolution patterns. The system learns: accuracy improves through automated learning from resolved tickets.
The impact: Instant 24/7 triage including after hours and holidays, freeing engineers from manual triaging while improving routing accuracy over time.
Customer Insights from Conversation Data
The problem: Understanding customer sentiment meant manually analyzing Intercom conversations. Traditional surveys captured only a small percentage of customer sentiment, and manual analysis took 1-3 weeks — by which point insights were already stale.
The solution: Automated monthly customer insights by connecting to customer communication platforms, extracting and analyzing relevant conversations using NLP, identifying themes, pain points, and feature requests, and compiling insights into comprehensive product development reports.
The impact: Transformed from a 1-3 week manual process to instantaneous generation. Product teams now have comprehensive monthly insights from all conversation data, not just survey responses.
SEO Content Production Pipeline
The problem: Content production was slow and labor-intensive. Creating a single article took half a day, including research, writing, SEO optimization, and publishing. The marketing team couldn't scale output without scaling headcount.
The solution: Integrated AI workflows that analyze search performance data, retrieve and analyze top-performing articles for target keywords, generate new content aligned with financial content guidelines, and implement strategic FAQ formatting for AI search optimization.
The impact: Content production time dropped from half a day to under 30 minutes — an 85% reduction. Organic traffic increased 20-30% through AI-driven dual-optimization for both traditional SEO and AI search engines.
"What began as a search for efficiency has evolved into a platform for innovation, proving that with the right tools, AI isn't just for engineers — it's for everyone."
Shawn Lim, "Democratization of AI", Medium (April 2025)
The Results
Scale & Adoption
Specific Improvements
| Area | Before | After | Impact |
|---|---|---|---|
| Content Production | Half-day per article | Under 30 minutes | 85% reduction |
| Organic Traffic | Manual SEO | AI-driven dual-optimization | 20-30% boost |
| Customer Insights | 1-3 weeks manual | Instantaneous | 100% coverage |
| Document Review | Manual validation | AI-powered OCR + LLM | Thousands of hours saved |
Contributing Back to the Ecosystem
Funding Societies actively contributes to the Activepieces ecosystem, embodying the spirit of open source:
- Submits pull requests for piece enhancements
- Develops custom pieces for unique requirements
- Provides detailed feedback for platform improvements
A Dedicated Role Was Created
The success of automation at Funding Societies led to creating a dedicated position: Senior Executive, Digital Process — a role focused entirely on driving and sustaining digital automation initiatives across Singapore business functions.
- →Design, build, and optimize workflow automations using Activepieces
- →Lead automation projects for product workflows
- →Collaborate with cross-functional teams on strategic automation initiatives
- →Maintain and enhance existing automation flows
Key Takeaways
About the Partnership
Funding Societies has been an Activepieces enterprise customer since early 2024, working closely with the Activepieces team on platform improvements, piece enhancements, and stability improvements. Their feedback has directly influenced product roadmap decisions including enhanced testing frameworks and enterprise stability features.