Precise market analysis

Edel Markets is live in Closed Alpha testing. The @CantonNetwork-native perps DEX, built for traders who need private positions, high-throughput execution, and institutional-grade market infrastructure. This is just the start. Apply for alpha access: markets.edel.finance

Our vision is to become the #1 player in every market we enter. We just announced Q3 plans: expansion into global banking and fintech, alongside humanoid robotics - and the release of SERV v2 in mid-July. Everything shipping in v2 is a direct answer to what banking demands before it trusts AI agents with real workloads. TLDR: The financial services AI agent investment cycle is starting right now, with hundreds of billions in spend coming. First movers among the banks stand to capture billions in extra profit while the latecomers get stuck with an uncompetitive cost structure. Adoption is being held back by two things - trust in agents and the cost of running them at scale. Those are the exact problems SERV was built to solve, and v2 is the biggest step we have taken toward solving them. Some key metrics and trends we are looking at: - Financial institutions are on track to spend $97B on AI by 2027, growing at a 29% CAGR - implying $200 B+ annually by 2030. - 83% of financial services professionals plan to increase AI spending. - McKinsey puts the value of AI in banking at $200-340 B per year. - Citi projects AI lifts global banking profits by $170B - 9% - by 2028, pushing sector profits toward $2 trillion. - BCG's 2026 estimate: AI can raise bank profitability by 30% and cut costs 30-40% by 2030. This is the trillion-dollar market we keep pointing at: AI adds $13T to global GDP by 2030, and banking's slice alone surpasses $150 B. Why the urgency by banks? Because the first-mover math is brutal. Banks that lead on AI gain a projected 4-point ROTE advantage over laggards. For a T1 bank, 4 points of ROTE is billions in extra profit, every year. Early adopters see 2.84x ROI on AI investment versus 0.84x for the laggards. In our research about 70% of banking executives believe AI will directly drive revenue growth while 32-39% of work inside financial institutions has high potential for full agent automation, another 34-37% for augmentation - up to 76% of all work, with cost reductions of up to 70% in some categories. The trend is clear. In 2025 alone, 50 of the world's largest banks announced over 160 agentic AI use cases. AI is being adopted faster than PCs, mobile phones, and the internet itself. The cycle has started. And yet almost nobody has actually deployed: 90% of enterprises want AI agents in production but only 11% have them there, with most deployments killed by unclear ROI and weak risk controls. A third of reported negative consequences from AI adoption come down to one word: unreliability. It is the most aggressive adoption curve of any emerging technology - and the largest gap between ambition and execution. Look closely at that gap and you will see why SERV v2 feature list is constructed the way it is: - Unclear ROI: Benchmark Tooling lets a bank measure cost savings and reliability gains on its own workloads before integrating anything. - Reliability: Shadow Agents verify every decision before it ships, pushing agent fleets toward 100% reliability - the only acceptable number where there is zero margin for error. - Contradictory rulebooks (in banking, this is called compliance): Multipath Reasoning lets agents reason through complex, conflicting rules in a single graph. - Cost at scale: Verification Hints and bounded reasoning cut re-work and tokens, so agents reach reliable decisions cheaper. - Security: Prompt Guard protects agents handling money from injection attacks, by default. With a lot happening behind the scenes, some of the work is already public. Our leadership already sitting in boardrooms with Tier 1 banks holding billions in collective assets. OpenServ on its way to securing certifications regulated markets require - unlocking pilots across banking and fintech, a $460B market in 2026. Neol running SERV Reasoning at 100% reliability in production with the UAE government. ThoughtProof - agent verification layer for banking, compliance, and onchain settlement - hitting 107x performance per dollar on SERV with zero failed calls. We believe this is the biggest economic shift since the steam engine, and financial services is where it lands first and hardest. SERV v2 exists so that when banking moves into AI - and it is moving now - it runs on OpenServ. The future is bright.