Wealth Management Platform for Asset Managers & Investors

We build an integration layer with adapters for each data source (custodian feeds, fund admin exports, market data APIs), normalizing everything into one internal data model — your existing systems stay in place.

We build extraction and normalization pipelines for capital calls, distributions, unfunded commitments, IRR/MOIC/TVPI, and K-1s, so this data lands in a structured, reportable format instead of being re-entered manually each quarter.

Yes — we design reporting engines around a template layer, so each client, family, or board gets their required format while the underlying data and calculation logic stay standardized and auditable.

Every recommendation, approval, and override — from IC memos to manager due diligence to portfolio changes — is logged with source data, rationale, and approver, so you can reconstruct why a decision was made months or years later.

We build role- and entity-level access control so family members, trustees, advisors, and internal staff each see only the data appropriate to their role — critical for family offices and MFOs managing trusts, SPVs, and multiple branches.

We build around your core systems (Aladdin, Charles River, Addepar, SS&C, etc.) using their APIs or data feeds — the goal is closing operational gaps, not a rip-and-replace.

This is the core OCIO/MFO trade-off — we separate the reporting template layer (client-facing, customizable) from the data and calculation layer (standardized, reusable), so each new client doesn't add proportional manual work.

We encode allocation ranges, restrictions, and client-specific rules into automated checks that flag violations before they reach a report or a client conversation.

Access control, encryption, and audit logging are built in from the architecture stage, not added later — aligned with SOC 2 Type II, ISO/IEC 27001, GDPR, and CCPA/CPRA requirements.

No. Client and portfolio data is never used to train external LLMs. Where AI models are used (document extraction, summarization, anomaly detection), we architect the pipeline so your data stays within your environment or a private, isolated instance — not shared with or absorbed into a vendor's general-purpose model.

Your data model, integrations, and infrastructure are built to be portable — not locked into a proprietary black box. You get full access to the underlying data schema and can export or migrate it without starting from scratch.

We roll out in phases — typically starting with one workflow or one asset class — so your existing reporting and reconciliation processes keep running in parallel until the new system is validated, rather than a single cutover that risks a missed reporting cycle.

We establish a single source of truth per data type (e.g., custodian as source of truth for positions, CRM for relationship data) and build synchronization rules so updates propagate automatically instead of creating conflicting versions across systems.

Scoped workflows — reconciliation automation, LP reporting, or an onboarding module — typically launch in weeks, with senior architect oversight and AI-assisted development speeding up delivery without cutting corners on compliance-critical logic.

We scope each engagement around a specific workflow with a measurable outcome (e.g., hours saved per reporting cycle, error rate reduction), so you have a concrete benchmark before committing budget beyond the initial phase — rather than an open-ended retainer.