Introducing Agent Builders
At Next Gate Tech, we have spent over six years solving the fundamental challenges that prevent investment fund operations from achieving true automation at scale.
We recognized early on that two structural barriers stand in the way. The first is data: scattered across custodians, administrators, counterparties, and internal systems, arriving in inconsistent formats, on different schedules, and with varying levels of quality. The second is workflow customization: even when data is clean and centralized, every firm applies its own operational logic, its own exception thresholds, its own escalation rules, and its own reporting requirements. Solving one without the other delivers limited value.
Since the start, we have tackled the first challenge head-on. We built our platform by leveraging the latest machine learning and AI methodologies to ingest, harmonize, and enrich operational data at scale, including portfolios, transactions, account balances, referential datasets, and more. Today we serve some of the largest players in the fund services industry such as BNP Paribas Securities Services or Amundi. This data foundation is what makes everything else possible. Now, with the launch of Agent Builders, we are solving the second challenge: customization at scale.
Introducing Agent Builders
We are shifting the paradigm from static AI features to a dynamic, agentic operating model. Agent Builders is a core platform capability that allows clients to assemble and deploy NGT Agents, standardized, configurable building blocks designed to automate complex investment fund operations. Rather than acting as "black boxes," these agents are transparent, governed, and reside entirely within your secure, isolated environment.
Core Features: The Anatomy of an NGT Agent
Every agent created through the Builder is defined by three primary elements that ensure it acts with precision and purpose:
- Persona: Defines the functional role, such as a NAV Oversight Specialist or Reconciliation Analyst.
- Knowledge Base: The specific set of authorized platform data objects (e.g., portfolios, transactions, market data) the agent can access.
- Action Set: The list of platform tools the agent is permitted to invoke, including calculators, validation sequences, and workflow routing.
Dual-Mode Execution
Our agents support two distinct ways of working to maximize operational efficiency:
- Interactive Mode ("Chat-to-Data"): Users can explore datasets and investigate anomalies using natural language queries like "Show me all funds with a NAV impact above 5bps."
- Autonomous Mode: Agents act as intelligent steps within automated workflows, triggered by events such as the arrival of new data or the detection of exceptions.
The Benefits: Why Agentic Intelligence?
By leveraging Agent Builders, firms can transition from "Human-in-the-loop" to "Human-on-the-loop" operations, where AI handles the heavy lifting of data analysis while humans retain final accountability.
- Accelerated Insight: Reduce "time-to-insight" by querying complex operational data without needing technical SQL or custom reports.
- Layered Intelligence: Our architecture combines deterministic logic for exact financial computations with Generative AI for interpreting results and explaining discrepancies.
- Scalability & Reuse: Use pre-configured templates for common scenarios (e.g., ESG Compliance, Root Cause Analysis) or build custom agents tailored to your proprietary methodologies.
Customization at Scale: Agents That Build Workflows
The fund industry operates under some of the most rigorous regulatory frameworks in financial services. Every calculation, every decision, and every exception must be traceable, auditable, and reproducible. This is a non-negotiable reality that any technology partner must respect.
At NGT, our agents do not replace deterministic workflows, they build them. This is the critical distinction. Rather than requiring weeks of manual configuration to translate a client's operational logic into platform rules, agents can now assemble, adapt, and deploy deterministic workflow sequences based on a firm's specific requirements. The computational logic that underpins NAV calculations, reconciliations, and compliance checks remains strictly rule-based and reproducible. What changes is the speed and flexibility with which these workflows are constructed and tailored.
The result is a dramatic reduction in configuration time and time to value on every deployment. What previously required extensive implementation cycles, mapping client-specific exception thresholds, escalation paths, validation sequences, and reporting logic, can now be achieved in a fraction of the time. For large-scale operations managing hundreds of funds across multiple jurisdictions, this ability to customize deterministic processes at scale is transformative.
Equally, for smaller firms operating with lean teams and complex operational requirements, this same capability removes the traditional dependency on costly, prolonged implementation projects, making enterprise-grade automation accessible regardless of scale.
Every action an agent takes is fully logged, every data source it accesses is recorded, and every decision path it follows can be retraced end to end. When a regulator or auditor asks "why was this result produced?", the answer is always available, clear, complete, and verifiable.
Security, Data Sovereignty, and Model Agnosticism
Data privacy is not just a feature of our platform, it is a foundational design principle. All agents operate within strictly segregated environments, ensuring absolute isolation between clients with no cross-client data access, no shared visibility, and no commingling of information at any layer of the stack.
Crucially, our framework is model-agnostic. While we provide native integration with enterprise-grade services like Gemini Enterprise, Agent Builders allow you to connect to your own internal LLMs or private cloud AI services. Your data is never used to train external models and remains firmly under your technological sovereignty. For firms operating under GDPR, DORA, or jurisdiction-specific data residency requirements, this architecture ensures that compliance is built in by design, not bolted on as an afterthought.