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AI to be effective in the energy market is a massive amount of data, and those systems are already there,” he explained. “But if AI is going to leverage them properly, we must restructure those systems.” While AI models are widely available, their real differentiator is industry-specific data. “AI models are commodities; you can use open-source options or rely on a major platform. But data? Tat’s unique to every industry.” Quesma’s approach centres on database proxies that
enable smooth migrations without disruption. “Te idea is to insert a proxy between databases, allowing organisations to transition without massive disruptions,” Migdał says. Rather than rebuilding from scratch, their model preserves legacy infrastructure while modernising operations. “We no longer live in a world where every system is built from scratch. It’s more like a renovation where old infrastructure, such as undocumented reports and legacy pipelines, still exists underneath.” Tis proxy-based system supports parallel operations,
minimising risk. “Instead of making one big switch, we allow businesses to run two systems in parallel, verify that the new one works, then transition gradually,” Migdał says. Tis staged approach mitigates performance bottlenecks and helps businesses pinpoint system failures efficiently. Quesma’s containerised proxy ensures seamless integration
between legacy and modern databases. “Te applications connected to the system won’t even realise the transformation is happening,” Migdał emphasised. “Tat’s how we enable incremental modernisation.” While some businesses temporarily adopt Quesma’s solution, many retain it long-term. By collaborating with database migration specialists and
leveraging AI-driven adaptability, Quesma continues to refine its technology, allowing businesses to modernise without disruption. “Some people want to keep their original database while plugging in new ones,” Migdał said. “You can mask these differences, preserve compatibility, and ensure applications still function correctly, because we sit in the middle.” AI-driven data translation enhances efficiency. “We use a combination of AI platforms, constantly testing and refining our models to optimise accuracy and performance,” he explained. Businesses hesitate to adopt new migration solutions due to
the risks associated with mission-critical systems. “Businesses are cautious. Teir systems are mission-critical, and switching to something unproven feels risky,” Migdał says. To mitigate these concerns, Quesma validates its technology in controlled environments before scaling to core applications. “We start small and validate the technology in manageable scenarios, before expanding into core business applications.” Rather than performing migrations directly, Quesma provides
tools that facilitate the process. “Our focus isn’t on performing migrations; it’s on creating solutions that facilitate them,” Migdał clarifies. Industry partners like Hydraulics appreciate Quesma’s seamless integration into existing infrastructures. “Many customers realise late in the process how difficult migration can be, and that’s when they bring us in,” he noted. Teir solution supports parallel system operations, helping mitigate risks. “Most transitions work
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without issue, but unexpected problems arise in about 5% of cases. Keeping the old system running allows us to troubleshoot without disrupting operations,” Migdał says. Quesma focuses on industry-specific applications like
Elasticsearch, ensuring optimised analytics instead of generic solutions. ClickHouse has become a key partner, referring migration cases to them. “With ClickHouse, our collaboration is more flexible, but they still direct certain accounts our way when businesses need migration support,” Migdał noted. AI is central to Quesma’s approach, particularly in query
translation and optimisation. “We use AI internally to generate rules for database queries. When we deploy these rules, we ensure they run efficiently and provide accurate results. AI helps identify patterns, but we also verify outputs manually to maintain reliability,” Migdał explained. AI extends beyond migration, enhancing visualisation and
business intelligence. “AI helps interpret natural language requests and refine visualisation styling so users get clear, meaningful insights,” he said. While Quesma currently relies on public APIs, they are exploring enterprise-level setups for on-premise AI models. “Currently, we use public APIs, but we’re considering enterprise-level setups where companies can run models locally,” Migdał explained. Quesma does not compete directly with visualisation tools.
Instead, it optimises the underlying data these tools rely on. “We’re not replacing tools like Tableau, we’re making sure the data it works with is optimised,” Migdał says. Expanding integrations with database vendors remains a priority.
“New database vendors like what we are doing because they see how our technology can unlock new database streams,” Migdał says. Yet, resource constraints mean careful project selection. “We are a small company, so we prioritise projects that we can deliver effectively. Tis could lead to more partnerships, similar to what we’ve done with Hydrox.” Looking ahead, balancing specificity with scalability is a core
focus for Quesma. Te company is already implementing new features, including query language and charting capabilities, which it plans to showcase at industry conferences.
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