We develop high-performance software that automates complex investment workflows and delivers superior client outcomes. We build the infrastructure that powers the next generation of wealth.
Move beyond basic chatbots to autonomous agents that act on your behalf. We integrate AI Agents to handle sophisticated tasks like real-time sentiment analysis and proactive portfolio adjustments.
Most popular agents are:
Your users don't need more charts. They need clarity. We build systems that pull together scattered data across banks, brokerages, and retirement accounts into one coherent picture, so users finally understand where they stand and what to do about it.
Analysis offers:
Move beyond static dashboards to a system that thinks, explains, and acts. We build multi-agent architectures that make complex financial data feel friendly and accessible, while staying within strict regulatory boundaries around financial advice.
It includes:
Technical debt shouldn't bottleneck your growth. We specialize in refactoring monolithic wealth platforms into scalable, cloud-native microservices. This approach to software modernization improves performance, reduces maintenance costs, and enhances security.
That's what we offer:
Check how forward-thinking financial firms are redefining wealth management with automation and intelligent systems built by our team.
6 months to AI launch
We transformed a US-based fintech platform from a passive tracking tool into an AI financial companion. Using Amazon Bedrock and Anthropic Claude, we built a dedicated Python agent that handles investment optimization via cyclic LangGraph workflows. AI Agent revisits and refines results across multiple iterations until portfolio goals are met. Meanwhile, a custom deterministic math layer guarantees 100% calculation accuracy. The AI now handles initial user onboarding and proactively identifies spending patterns for the users.
Single source of truth for portfolio analytics
A venture fund needed a centralized way to aggregate and analyze portfolio company metrics, eliminating the need for analysts to manually collect data. We developed a comprehensive internal dashboard using Retool. The platform automates tracking of key performance indicators and includes a dedicated module for monitoring employee headcount and team structures across companies.
Leverage cooperation with a team that deeply understands the intersection of global capital markets and high-performance automation.
We design high-density UI/UX that allows advisors to visualize global portfolios and execute high-stakes decisions without cognitive overload or dashboard fatigue.
Our platforms are engineered to meet strict regulatory standards. They are powered by zero-trust architectures, encrypted data vaults, and audit-ready reporting.
Our fintech development teams know the nuances of wealth management, from risk profiling to complex API integrations with legacy banking cores and market data providers.
You retain 100% ownership of your source code and proprietary AI models. We build your software and hand over the keys to your new digital asset.
By integrating agentic AI in wealth management, we enable your platform to perform high-fidelity tasks with zero latency.
In AI wealth management software development, our engineers create systems that don't just provide a recommendation but also document the reasons behind it.
We deliver quality without compromises.
Navigate the complexities of the modern fintech ecosystem with custom-built software tailored to your specific market needs.
Centralized platforms provide 360-degree asset visibility and automated performance tracking. As a result, financial advisors can oversee complex portfolios with AI-driven precision.
Our developers build data-rich CRMs designed specifically for wealth advisors. The system unifies client data, portfolio performance, and actionable insights into a single command center.
We develop high-density data visualization and interactive client dashboards that turn fragmented market data into actionable insights.
Our secure mobile and web banking solutions bridge the gap between high standards for institutional reliability and modern user expectations.
Digital-first core banking engines and modular architectures empower agile startups to launch and scale niche financial products.
Automated credit decisioning and risk-based loan management systems accelerate the underwriting lifecycle and maintain strict capital integrity.
We engineer your custom platforms using a precision-selected tech stack optimized for agentic AI integration and real-time data processing.
At Akveo, we offer engagement models that align with your project's complexity and organizational maturity.
When choosing this model, you access our senior-level engineers with niche expertise in agentic AI, high-density fintech UI/UX, or complex API orchestration. Staff augmentation helps instantly boost your development velocity.
Best for: Teams looking for specific technical expertise
You can hire a full-scale engineering department that operates as a seamless extension of your firm. This model is built for long-term product evolution, where deep domain knowledge of wealth workflows and compliance is vital.
Best for: Scaling institutional wealth management projects and multi-year roadmaps
Delegate the entire technical lifecycle of a specific wealth management objective to us. We can take full ownership from initial architectural design to secure deployment and provide you with predictable timelines and budget transparency.
Best for: AI-driven MVPs, legacy core modernization, and high-impact feature launches
70% of our partners continue working with us for more than 2 years.
Timelines greatly depend on the complexity of your project. A specialized module (like a client portal) can be production-ready in 3 months. Meanwhile, the development of a full-scale portfolio management ecosystem powered by AI automation typically takes up to 9 months or more. At Akveo, we move faster than the standard hiring cycle. You get a technical estimate within 48 hours, and we can kick off your project in just 7 days.
AI functions as an architectural layer that eliminates manual data entry and identifies hidden risks. For instance, we rely on AI models to automate portfolio rebalancing based on real-time market shifts and client risk profiles, introduce predictive analytics that detect at-risk clients before they churn by analyzing engagement patterns, and implement hyper-personalization that generates custom investment reports for thousands of clients in seconds.
Development costs vary based on your specific requirements. Most high-concurrency systems fall into a few clear brackets. Specialized modules and MVPs typically start between $50K and $80K. Full ecosystems usually land between $150K and $500K or more. For annual maintenance, budget around 15 to 20% of the initial build cost to cover security patches and infrastructure scaling.
Our process runs in six stages: discovery to align goals with regulatory requirements, security blueprinting to embed zero-trust protocols from the start, prototyping to design intuitive high-density interfaces, engineering to build features and connect third-party services, and rigorous QA, including penetration audits for bank-grade protection. After deployment, you retain 100% ownership of the code and AI models.
