SimCorp Unveils Agent Launchpad for Investment Managers

SimCorp has officially launched Agent Launchpad, a new agentic AI ecosystem designed to help investment managers discover, deploy, and orchestrate AI agents directly within its SimCorp One platform. The announcement came during the company's annual client conference in Copenhagen, where roughly 1,400 financial services leaders gathered to witness the unveiling.

The platform provides clients access to pre-built AI agents developed by SimCorp and vetted partners, covering workflows including portfolio management, corporate actions, risk analysis, and operational support. Clients can also construct their own agents using data from SimCorp One alongside approved third-party sources. This collaborative approach is intended to help automate operational processes, speed up market analytics, and support investment decision-making.

According to the official press release, Agent Launchpad builds on SimCorp One's unified data layer, enabling multiple AI agents to operate in tandem across investment workflows within a shared governance framework. Each agent interaction produces a structured audit trail recording which data informed outcomes, what constraints were in place, and which agents were involved, with humans retaining accountability for final decisions. SimCorp will also introduce a prompt library to help clients begin working with agentic AI more readily.

The official announcement confirms that research platform Orbit will become the first ecosystem partner to offer an agent through Agent Launchpad. The FinTech, which provides AI-driven research and intelligence tools for financial services firms, will embed insights spanning company fundamentals, markets, news, broker research, and regulatory information directly into SimCorp One workflows.

CEO Peter Sanderson emphasized the orchestration angle during the announcement. "Agent Launchpad provides the connective layer that allows AI agents — whether from SimCorp, a trusted partner, or built by the client — to collaborate across real investment workflows, safely, consistently, and at scale, while maintaining the controls and data integrity our clients require." He added that investment managers will get a higher return on their AI investments when their agents are orchestrated and working together — not operating in isolation.

Orbit founder and CEO Da Wei noted the partnership brings Orbit's AI-powered research directly into the daily workflows of leading asset managers and asset owners. "Together, we are making advanced AI insights accessible in a way that is aligned with institutional investment requirements."

Independent reporting from FinTech Global corroborates the timeline and scope of the changes, noting the platform's emphasis on governance and audit trails. This matters because institutional investors don't just want AI that works — they need AI that can be explained, audited, and defended during regulatory reviews.

Consider the physical reality of this. An investment analyst clicking through SimCorp One will now see agent-generated insights appear alongside traditional portfolio data. The interface doesn't just spit out predictions — it shows which data informed the outcome, what constraints applied, and which agents participated. That audit trail isn't a nice-to-have; it's the difference between a tool that gets adopted and one that sits gathering digital dust in compliance's shadow.

Context matters here. A January 2026 study commissioned by SimCorp found that 70 percent of buy-side firms are successfully employing AI to support their front office. This marks a significant increase from last year's report, which showed only about 10 percent of respondents were actively exploring AI tools. The shift from pilots to business-critical applications is real, but it's also creating new problems. (Nobody wants to explain to a board why their AI agent made a decision based on yesterday's data.)

The same study revealed that vendor stability ranks as the most important criterion when evaluating AI solutions for investment management — ahead of features. Firms consider vendor stability the top priority when selecting third-party AI solutions for their investment management. This explains why SimCorp is emphasizing its established position rather than competing on flashy features alone.

For the first time in three years, innovation has become the leading driver of technology and operations investments. Achieving competitive differentiation through innovation now surpasses operational efficiency and controlling operating costs as the leading driver of technology and operations investments for 2026. The market is shifting, and SimCorp is positioning itself to capture that shift.

Agent Launchpad was unveiled at SimCorp Global Summit, the firm's annual client conference, this year held in Copenhagen, April 22-24. The first SimCorp One clients are expected to gain access this year. Whether that access translates to meaningful adoption remains the real question.

The technology itself isn't revolutionary — agentic AI has been discussed for years. What's different is the orchestration layer. SimCorp is betting that investment managers don't need another standalone AI tool; they need agents that work together within their existing workflows. That's a harder problem to solve, but also a more valuable one if executed properly.

First clients will likely test the waters with pre-built agents before attempting custom builds. The prompt library will help, but institutional adoption moves slower than tech enthusiasts prefer. Expect initial deployments to focus on operational support and risk analysis rather than core portfolio decisions. Humans aren't handing over the keys anytime soon.

Whether investment managers actually pay for this remains the real question. The platform adds value, but the financial services industry is notoriously cautious about new technology spending. SimCorp has the client base and the platform, but adoption will depend on whether agents deliver measurable ROI beyond what existing tools already provide.

Artūras Malašauskas is an AI Systems Integrator with 20+ years of production-grade web engineering experience. He has designed, shipped, and scaled enterprise Python/PHP systems for logistics, SaaS, and public-sector clients. For the past year, he has focused exclusively on AI integrations: deploying open-source LLMs, building generative media pipelines (image, audio, video), and engineering multi-agent workflows for real production environments. His standard: reproducibility, security, cost-efficient inference—no vaporware. He documents and evaluates emerging AI tooling, separating verified capabilities from marketing noise. Technical editor at: muza-ai.eu, ai-verslas.lt, ai-naujinos.lt Connect on LinkedIn