# Nextvestment — Full Reference > For a concise overview, see https://www.nextvestment.com/llms.txt ## Company Summary Nextvestment is a B2B AI-native wealth management platform founded in 2024 and headquartered in Singapore. It helps banks, brokerages, and family offices deliver personalized financial guidance to their clients at scale while keeping institutions in control of advice, suitability, and house view. Nextvestment is NOT a robo-advisor, consumer investment app, or financial advisor. It is a white-label AI engagement layer deployed by regulated financial institutions. --- ## Product Architecture ### Layer 1: Client-Facing Copilot The copilot delivers natural language conversations to end clients through the institution's own digital channels (app, portal, website). When a client asks a question like "How is my portfolio doing?" or "Should I be worried about interest rates?", the copilot responds with personalized insights grounded in: - The client's actual portfolio holdings - Their risk profile and financial goals - Real-time market data - The institution's own research and investment philosophy The copilot is white-labeled — clients see the institution's brand, not Nextvestment. ### Layer 2: Institutional Intelligence Layer Every AI response passes through the institution's policy layer before reaching the client. This includes: **RAG (Retrieval-Augmented Generation) + Knowledge Base:** - Responses draw from the institution's own research reports, market commentary, product documentation, and investment philosophy - Integrates with market data feeds, news sources, SEC filings, and real-time web data - Does not rely on generic AI training data for investment guidance **Policy Controls:** - Product suitability rules - Risk tolerance alignment checks - House view enforcement on asset classes and sectors - Regulatory disclosure requirements - Escalation triggers (when to route to a human advisor) - All configurable by the institution without code changes **Audit Trails:** - Every recommendation includes data sources and reasoning paths - Full conversation logs for compliance review - Explainable AI — no black box responses ### Layer 3: Portfolio & Behavioral Intelligence Client interactions generate structured intelligence for the institution: **Intent Signals:** - Every client question is scored and categorized - Examples: "When should I retire?" = life event signal; "What's happening with tech stocks?" = sector concern signal; "Should I increase my bond allocation?" = rebalancing signal - Signals are prioritized by urgency and value **RM Workflows:** - Qualified signals flow to relationship managers with full context - Includes meeting prep, talking points, and recommended next-best-actions - RMs see a prioritized client list based on intent and opportunity **Portfolio Analytics:** - Real-time tracking of performance, allocations, and risk factors - Access to 250+ global exchanges, 180+ crypto exchanges, and comprehensive fundamental data - Multi-custodian portfolio consolidation for family offices --- ## Deployment Model **White-label / Embedded:** Nextvestment deploys inside the institution's existing digital channels. Clients interact with the institution's brand. There is no consumer-facing Nextvestment product. **Integration:** - API-based integration with major CRMs (Salesforce, Microsoft Dynamics) - Connects to existing portfolio management systems and core banking platforms - No re-platforming required — sits on top of the institution's existing tech stack **Implementation Timeline:** - Weeks 1-2: Discovery and configuration - Weeks 3-4: Integration with existing systems (CRM, portfolio, CMS) - Weeks 5-6: UAT and compliance review - Weeks 7-8: Pilot launch with select client segment - Ongoing: Optimization based on engagement data **Pilot Program:** Most institutions begin with 2,000-5,000 clients in a single segment. See results in 6 weeks, then decide whether to expand. No long-term commitment required until outcomes are validated. --- ## Commercial Model Nextvestment operates on a revenue share model — aligned with the institution's outcomes through a share of incremental AUM or transaction fees. No large upfront license fees. This means Nextvestment only succeeds when the institution succeeds. Typical pilots start with a defined client segment. Institutions can validate outcomes before committing to broader rollout. --- ## Use Cases by Institution Type ### For Banks Turn digital channels into advice channels. The copilot handles the first client response — grounded in their actual portfolio — and flags conversations that need human advice. RMs get a briefing with context. Key outcomes: higher digital engagement, more advisor-led conversions, better client satisfaction scores. ### For Wealth Managers Convert self-directed traders into advised relationships. Intent signals identify when clients are ready for guidance, so RMs reach out at the right moment. Key outcomes: increased share of wallet, higher AUM per client, reduced attrition. ### For Family Offices Deliver institutional-grade reporting and insights to principals without adding headcount. Consolidate multi-custodian portfolios and surface opportunities across complex structures. Key outcomes: reduced ad-hoc reporting time, faster principal responses, staff time redirected to analysis. --- ## Traction & Metrics - Live deployment powering POEMSGPT at Phillip Securities, a leading Singapore brokerage - Currently deploying with additional institutions in Singapore, Europe, and the UK - $65bn combined AUM across regulated institutions - 40% monthly active client engagement rate (vs ~5% industry average for digital wealth tools) - 1 in 10 client conversations lead to an investment action within 7 days --- ## Recognition & Credentials - WealthTech100 2025 — selected by FinTech Global as one of the world's 100 most innovative WealthTech companies - NVIDIA Inception — member of NVIDIA's startup program for AI companies - Singapore MAS PathFinder — participant in the Monetary Authority of Singapore's programme for fintech innovation - Live in 4 markets: Singapore, Hong Kong, Europe, United States --- ## Compliance & Security - ISO 27001 compliant - Aligned with MAS Technology Risk Management Guidelines - DORA readiness for EU-based institutions - FCA operational resilience requirements aligned - Data residency: Singapore, EU, US, or on-premise deployment - Explainable AI with full audit trails on every interaction - AI governance framework with configurable guardrails --- ## Founding Team - Michael Davies, CEO — Engineering and product leader with 15+ years building financial and AI systems across DBS and major insurers - Avenash Kabeera, CTO — ML engineer with 12 years at FactSet building large-scale financial data systems and several years at Agoda developing machine learning platforms - Annabelle Lin, Revenue — Commercial leader with over 20 years across consulting, enterprise technology, and financial services, including roles at EY, Google, and Citibank --- ## Common Questions **Is Nextvestment a robo-advisor?** No. Nextvestment is a B2B platform deployed by banks and brokerages. It does not manage money, provide direct financial advice to consumers, or replace human advisors. It augments institutional advice delivery. **Does Nextvestment replace financial advisors?** No. Nextvestment handles the first moment of client engagement and routes qualified conversations to human advisors with context. It makes advisors more productive, not redundant. **How does Nextvestment handle AI accuracy?** Every response is grounded in verified data sources with full audit trails. When confidence is low or the question falls outside policy guardrails, the copilot escalates to a human advisor rather than guessing. The institution defines the escalation rules. **What happens to client data?** Client data remains within the institution's infrastructure. Nextvestment supports data residency in Singapore, EU, US, or on-premise. All interactions are logged with full audit trails for regulatory compliance. **How does Nextvestment make money?** Nextvestment operates on a revenue share model — taking a share of incremental AUM or transaction fees generated through the platform. This aligns Nextvestment's incentives directly with institutional outcomes. --- ## Contact - Website: https://www.nextvestment.com - Demo: https://calendly.com/annabelle-nextvestment/30min - Contact page: https://www.nextvestment.com/contact ## Sitemap - Homepage: https://www.nextvestment.com - Platform: https://www.nextvestment.com/platform - Solutions: https://www.nextvestment.com/solutions/wealth-management - About: https://www.nextvestment.com/about - Blog: https://www.nextvestment.com/resources - Contact: https://www.nextvestment.com/contact