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AI & Technology

From Software House to AI Company — Lessons from Enersys’s Transformation

The real story of Enersys, from a one-person software company founded in 2012 to an AI Company serving leading organizations in Thailand—plus lessons and practical guidance for companies looking to transition into the AI era.

25 Feb 20267 min
AI TransformationSoftware CompanyStartup ThailandEnersysGenesis AIDigital Transformation

In Thailand’s technology industry, many software houses are asking the same question: “How do we survive in the AI era?” Some fear AI will replace them. Others want to change but do not know where to begin.

In this article, we share the real story of Enersys—a Thai software company that started as a one-person business in 2012, grew into a 15-person team, earned the trust of leading organizations across the country, and is now transforming into an AI Company with products of its own. We hope these lessons will be useful for Thai technology companies seeking direction in the age of AI.

The Beginning: One Person and a Belief in Open Source (2012–2015)

In 2012, Tomz, the founder of Enersys, started the business alone, leveraging expertise in open-source ERP systems such as Odoo (then known as OpenERP). At a time when Thailand’s ERP market was dominated by SAP and Oracle, with price tags ranging from millions to tens of millions of baht, choosing Odoo was a risky move—but one that opened access to mid-sized customers seeking high-quality ERP systems at a reasonable cost.

In the early years, the business focused primarily on consulting: helping clients analyze requirements, design systems, customize Odoo, and implement successful deployments. Each project typically took 3–12 months, and revenue depended on how many projects the company could deliver.

The key lesson from this stage was that specialized expertise is what allows small companies to compete with larger players. You do not need to be good at everything—only exceptionally good at something the market needs and struggles to find.

Building a Team and Earning Credibility (2015–2020)

As the company’s work began to prove itself, clients grew larger. Enersys earned the trust of leading organizations across multiple industries, including energy, financial services, media and entertainment, real estate, government, and agriculture.

Working with these organizations did more than generate revenue—it built experience that could not be gained elsewhere. Every project became a lesson in complex requirements, large-enterprise workflows, legacy system integration, and managing multiple stakeholders.

During the same period, Enersys also raised its organizational standards by earning Odoo Silver Partner certification, a global validation of its Odoo capabilities, as well as ISO/IEC 29110-4-1:2018, a software development process standard for small organizations.

The team grew from 1 to 15 people, with each member carefully selected and developed into a domain specialist. The lesson from this stage was that certification and track record open doors to new opportunities—but what brings customers back is the actual quality of the work.

The Turning Point: Recognizing the Limits of the Service Model (2020–2023)

Although the software consulting business continued to grow, Tomz began to see the clear limitations of this business model.

The first issue was that revenue was tied to time. Income depended on the number of hours the team could work. To increase revenue, the company had to hire more people—which then required finding more projects to keep them busy. This cycle did not scale.

Implementation projects also tended to end as one-off engagements. There was some ongoing maintenance revenue, but not enough to create long-term stability. There was no true recurring revenue.

And with every project delivered, the knowledge and code accumulated inside the customer’s project—not as assets owned by the company.

When ChatGPT emerged in 2022, the picture became even clearer: much of the development work that once required people would increasingly be supported by AI. In the future, customers would be willing to pay less for software development.

Recognizing these limitations was the starting point of the transformation.

The Transition: From Service to Product-Led (2023–2026)

Enersys chose a clear strategy: shift from Service-First to Product-Led, using more than 14 years of experience working with enterprises to build products that solve real problems.

Genesis AI Platform

Enersys’s flagship product in this new era is Genesis AI, an Agentic AI platform for enterprises designed around real customer pain points.

Genesis AI is not just a chatbot. It is an AI agent system that can connect to enterprise data and internal systems, retrieve information from internal documents (RAG), plan and execute assigned tasks, and work alongside ERP and other business systems.

The name Genesis means “a new beginning,” reflecting both a new chapter for Enersys and a new beginning for the organizations that adopt it.

PrivacyHub

Another product born from real-world customer challenges is PrivacyHub, a platform for PDPA (Personal Data Protection Act) management.

When the PDPA came into effect, many organizations needed a system for managing personal data in compliance with the law. PrivacyHub addresses this need by enabling organizations to maintain ROPA (Record of Processing Activities), manage cookie consent, handle DSARs (Data Subject Access Requests), and manage data breaches—all in one place.

5 Key Lessons from the Transformation

Based on our experience, these are the lessons we want to share.

Lesson 1: Do Not Wait Until You Are 100% Ready

If you wait for everything to be perfect, you will never start. Enersys began developing Genesis AI while continuing to run consulting projects in parallel. Service revenue was used as fuel for product development. The company did not stop all service work and switch to product overnight.

Lesson 2: Service Experience Is a Goldmine

Startups that begin from zero do not have what we have.

The knowledge accumulated from more than 100 projects, the insights into the challenges faced by Thai enterprises, and the understanding of real operational processes—these are the most valuable assets for building products that solve real problems.

Lesson 3: Choose the Problem You Understand Most Deeply

Enersys did not try to build AI that does everything. Instead, it chose to focus on Enterprise AI—using AI to solve organizational problems—which is the area we understand most deeply from more than a decade of experience.

Lesson 4: Small Teams Can Do Big Things

With a team of 15 people, Enersys can build enterprise-grade products because we use AI to multiply the team’s capabilities:

  • Developers use AI to help write and review code
  • The sales team uses AI to help prepare proposals
  • The support team uses AI to help respond to customers

We are living proof that AI enables small teams to perform at the level of much larger ones.

Lesson 5: Product Must Come with Service, Not Replace It

Becoming Product-Led does not mean abandoning service altogether. On the contrary, enterprise customers in Thailand want both a strong product and strong service together. Genesis AI is not just SaaS that customers sign up for and use on their own—it comes with consulting, onboarding, training, and comprehensive support.

Looking Ahead

The transformation is not finished—and it may never truly be, because technology will continue to change. What Enersys has learned is that the ability to adapt matters more than a perfect long-term plan.

For software houses in Thailand that are looking for direction, our advice is this: do not see AI as a threat; see it as an opportunity. Use the experience you have accumulated to create new value. Start with what you do best, then integrate AI into it.

Transformation does not have to be a massive leap. It can be a series of small, consistent steps—just do not stop moving.

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Transforming Futures."

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