Transform fragmented investment, client, and risk data into actionable, AI-ready products—enabling faster, smarter decisions across equities, fixed income, and tax-saving solutions.
With SCIKIQ, asset managers can contextualize and monetize data across portfolios, clients, compliance, and operations—accelerating growth, protecting margin, and sharpening your competitive edge in a rapidly digitizing market.
Captured from 23 sources across strategy, leadership, lines of business, competition, geographies, capabilities and recent signals — and used to ground everything below.
The maturity curve runs from visibility, to explanation, to natural-language reasoning, to action — and each step depends on the one before it.
Consolidate siloed data from client onboarding, portfolio management, compliance, and transaction systems to deliver a real-time, unified view of AUM, inflows, outflows, and risk exposures.
Growth & EfficiencyModel relationships between clients, portfolios, products, transactions, and regulatory events to pinpoint drivers of churn, compliance breaches, or margin compression.
Risk & ComplianceEmpower teams with an LLM-powered copilot that answers queries like 'Why did redemptions spike in ELSS funds last quarter?'—grounded in your actual data and context.
Competitive EdgeDeploy autonomous agents to proactively address compliance gaps, optimize asset allocation, or accelerate KYC remediation—closing the loop from insight to action.
Profitability & ComplianceBuilt bottom-up, because trust compounds upward: agents are only as safe as the copilot's grounding, the copilot only as reliable as the graph, the graph only as complete as the 360° model beneath it.
Break down data silos across investment, client, and regulatory systems for a single source of truth.
Model relationships and dependencies across investors, portfolios, transactions, and compliance events.
Conversationally explore investment, risk, and client data—grounded in your real context.
Autonomous agents to execute remediation, optimization, and compliance actions directly in your source systems.
Data remains in your existing systems—SCIKIQ integrates business concepts across investment, client, and compliance domains, not just technical feeds.
200+ pre-built connectors ingest data from Fund Admin, CRM, Portfolio Mgmt, and regulatory systems.
Enrich and tag data with business context—client risk, product type, compliance status.
Entity resolution and modeling unify clients, portfolios, transactions, and compliance events.
Lineage, quality, and access controls ensure compliance and auditability across the data fabric.
Unified profile of each client—AUM, product holdings, compliance status, and engagement.
End-to-end view of each product—flows, redemptions, risk, and performance.
All compliance events, KYC status, and regulatory breaches in one lens.
Holistic view of client and aggregate portfolios—allocation, risk, and returns.
Track all retention and acquisition campaigns, client targeting, and outcomes.
SCIKIQ delivers a unified, AI-ready data fabric in under 6 months, with 200+ pre-built connectors and 85% faster integration—avoiding the multi-year, high-risk investment of custom builds.
Goes beyond dashboards—contextualizes data into a knowledge graph and activates it with AI copilots and autonomous agents, closing the loop from insight to action.
Purpose-built for asset management: models client, product, compliance, and campaign 360s, not just raw data—enabling business-first, regulatory-compliant activation.
Answers are grounded in your real data, lineage, and context—no hallucinations, full auditability, and explainable AI for board and regulator confidence.
When the four layers are in place, leadership sees a single live view — every number traceable to its source, every alert to its root cause.
Entities and their typed relationships as one connected, physics-driven graph. Drag nodes, scroll to zoom, click to inspect — or trace the live scenario from root cause to business outcome.
Ask your business-critical investment, compliance, and client questions in plain language—grounded in your real data context. Language models supply the fluency; the graph supplies the truth.
Every agent draws on the same graph and semantic layer — then closes the loop with a real transaction in the source system.
“Can we trust it?” — answered by design, not by promise.
Every leader sees themselves — each use case builds on a business 360 and the four pillars it needs: 1 Enterprise 360 · 2 Knowledge Graph · 3 AI Copilot · 4 Agent Factory.
Unify client, product, and inflow data to identify at-risk segments and trigger targeted campaigns—driving new investments and protecting margin.
Surface and resolve compliance breaches before they escalate, with full lineage and agent-driven remediation.
Model scenario impacts of tax regime changes and reallocate flows to alternative products, maximizing retention and growth.
Automate KYC remediation and onboarding, reducing cycle time and cost while improving client experience.
Link campaign outcomes to real client and product data, enabling AI-driven targeting and measurement.
Built once, the context layer becomes shared infrastructure — so each new AI initiative starts from enterprise context, not a blank integration backlog.
We would prove the context layer in three focused sprints — earning the right to scale with evidence, not slideware.
Rapidly connect source systems and build the first Customer/Product/Compliance 360s.
Layer business context and deploy the AI Copilot for semantic Q&A.
Deploy autonomous agents to close the loop from insight to action.
One unified, AI-ready data foundation powering growth, margin, compliance, and operational agility—delivered in under 90 days.