Bring Intelligence Into Your Workspace, On Your Terms
Add an agentic AI layer to your data, documents, workflows, and systems without losing control.
AI-Powered Enablement
Structured Extraction
Convert PDFs, emails, reports, and notices into structured records linked to your data models.
Data Structuring
Standardise fund, sub-fund, share class, and instrument data across heterogeneous sources.
Smart Data Handling
Detect structures, fill gaps, harmonise inputs, and infer missing attributes.
Reconciliation Support
Identify inconsistencies, breaks, and anomalies requiring review.
Contextual Investigation
Provide explanations and context to support oversight and validation workflows.
Vector Search
Retrieve relevant entities across inconsistent formats using relationship-aware search.
Full Control How and Where AI is Used
AI runs inside the same client-segregated environment as your data, storage, and services, with no cross-client visibility.
AI only processes the fund data, transactions, documents, and metadata you uploaded or generated, with optional anonymisation or pseudonymisation.
Data processed by AI is never reused to train shared or external models.
AI relies on enterprise-grade services with encryption, access control, logging, and the same governance model as the rest of the platform.
Enable, restrict, or disable AI at product, client/workspace, feature, or workflow level — including full opt-out.
Plug in your own approved LLMs or AI services within your isolated workspace, with AI usage scoped contractually if required.
Build Your Own Agents
Agent Builder Studio
Configure agent roles, instructions, and objectives (e.g., Oversight Investigator, Reconciliation Analyst, Onboarding Assistant) with reusable templates.
Human-in-the-Loop by Design
Require review/approval steps for sensitive actions (e.g., publishing, sending, updating) while keeping agent outputs explainable and traceable.
Versioning, Testing, and Monitoring
Iterate safely with agent versions, test runs/simulations, and observable runs so production behavior stays predictable over time.
Embed AI Directly Into Your Workflows
AI Actions in Workflows Use actions such as Extract Unstructured Data, Enrich Data, Classify File, Reconcile Data, Predict Schema.
Human-in-the-Loop Present AI suggestions as tasks, reviews, or validations inside collaboration dashboards.
Agentic Workflows Combine rules, data, and AI steps to perform multi-stage operational processes.
Trigger-Based Execution Invoke AI on file reception, record creation, schedules, or manual triggers.
Explainable Outputs Review, accept, override, or amend AI results as part of normal operations.
Full Traceability Track AI inputs and outputs back to source data and workflow steps.
Connect to Your Systems and Tools
External System Integration
Invoke AI within workflows that send or receive data via APIs, events, or files.
Internal Tool Connectivity
Query databases, storage, and internal tools as part of AI-assisted processes.
Upstream Data Ingestion
Pull data from custodians, market feeds, and providers before AI structuring or validation.