Mutual Funds. Six workloads, one endpoint.
Asset management companies, RTAs & distribution — the workloads below need more than one data model at once, which is exactly why they stall on a stitched stack.
Asset management companies, registrars and transfer agents, national distributors and MFD platforms operating at retail scale across India.
The forcing function.
Indian mutual fund AUM more than doubled in five years, investor accounts are at a record high, and SEBI has opened the category to new entrants — competition is shifting to service quality and distribution intelligence. At 27 crore folios, the fund house that can answer “which distributors are about to lose SIPs” in seconds holds a market-share advantage over the one that files a BI request.
The distribution graph — net sales originate through ARN hierarchies and sub-broker chains, not where they are booked.
Indian MF industry AUM at March 2026 — more than doubled in five years (AMFI)
investor accounts; ₹32,087 crore monthly SIP inflows — March 2026 (AMFI)
SEBI approvals expanding the field — service and data become the differentiator
Six workloads, five query shapes.
Almost no workload here needs only one data model — which is why single-model databases deliver it only with a second system and a sync problem.
Model ARN hierarchies, sub-broker chains and platform relationships as a graph, joined with live flow data — see where net sales actually originate, not where they are booked.
Commission spend redirected to genuinely productive channels; faster reaction to flow shifts.
Score every folio for stoppage risk using behavioural similarity to previously churned investors, joined with live transaction and market context.
Retention intervention before the mandate is cancelled — where the economics are decisively better.
Semantic and full-text retrieval across portfolios, factsheets, commentaries and filings, so sales and research teams can ask comparative questions in plain language.
Sales enablement without a research bottleneck; consistent, sourced answers in the field.
Folio-aware self-service — account-specific questions answered by joining semantic retrieval over process documentation with the investor's own live RTA record.
Sharp reduction in RTA call volume and cost per investor interaction.
Find investors resembling the ideal holder of a new scheme using embedding similarity over holding and behaviour profiles, expanded through the distributor graph.
Higher NFO collection per rupee of campaign spend; better post-launch persistency.
Detect churn patterns, unsuitable switches and concentration anomalies across the distribution network as graph patterns rather than one-off exception reports.
Issues surfaced internally ahead of regulatory attention; distribution risk quantified.
Impact statements are directional targets referenced to published industry research — calibrate against your own baseline.
The stack this replaces in Mutual Funds.
Five licences, five sync jobs, five security perimeters — collapsed into one atomic store.
Flows, folios, distributors and research in one query — the operating requirement for competing at 27 crore accounts.