Consider a small mystery on a trading desk. A client reads a research note, attends a company meeting and then sends an order. Three useful facts. Put them in three different systems, however, and the salesperson may learn about them in the wrong order, or after the next call. The relationship is active. The record of it is scattered.
- Prism connects sell-side client activity with business performance.
- Datazoic reports 92% adoption and more than 1,500 active users.
- Its AI proposition depends on the client data underneath it.
Datazoic builds software for this particular information problem. Its customers operate on the sell side of capital markets: investment banks, broker-dealers and research firms serving institutional investors. Their work produces calls, research reads, meetings, trades and commissions. Datazoic wants those traces to become a usable memory of the client, available while a decision can still change.
01 / The number before the model
The company's attention-grabbing number is 92%. That is its reported user adoption rate, set against a claimed 30% average for generic CRM deployments. These are vendor figures, rather than a controlled comparison. Even so, the choice of headline metric tells you something about the business: a client database cannot become intelligent if the people who know the clients keep avoiding it.
Prism, Datazoic's CRM platform, is built around research, sales, trading, corporate access and investment banking. Interactions attach to accounts and contacts; coverage activity can sit beside revenue and resource use. The company's product page puts its premise plainly: “Clean data requires consistent input.” The design question follows: how much extra work must someone do to supply that input?
Reported Prism user adoption
Two products answer with familiar surroundings. Blast runs research distribution inside Outlook, linking sends and readership to CRM records. Prism Anywhere provides mobile and embedded access: find a contact, log a meeting, send research, check revenue. The practical appeal is fewer occasions to postpone an update until somebody gets back to a desktop.
02 / What a busy client costs
Activity alone is a misleading measure of a relationship. A client can consume research, request analyst time and attend events without generating enough revenue to cover the attention. Datazoic Analytics puts client profitability alongside wallet share and commission attribution. It draws on the systems generating the work, including order management, commissions, expenses, research distribution and voice or video activity.
Wallet share asks how much of the client's commission budget reaches the desk. Profitability sets attributable revenue against coverage costs. Attribution connects trading with the interactions that preceded it. Datazoic also says it incorporates Coalition Greenwich benchmark data. These views give a manager more to examine than a count of calls, although an observed sequence still requires judgment about what caused a trade.
03 / The meeting after the meeting
Corporate access supplies a particularly good example. Arranging a meeting between investors and company management creates an obvious scheduling task. It also creates a less obvious accounting task: months later, can the firm show which service it delivered to which client? An invitation list and an attendance record answer different questions.
Event Manager handles meeting slots, venues, investor attendance and corporate guests while recording event activity in the CRM. Consumption Hub carries Prism interactions, readership and corporate access activity into configurable broker vote reports. Those reports help document service for client evaluations of research providers. The useful detail is the connection: the meeting record has somewhere to go after the room empties.
Investment bankers get a different arrangement of the same idea. Deal Manager brings pipeline status, banker coverage, fees, mandates and call reports into a connected workflow. Datazoic describes it as source-agnostic, able to connect the data providers a desk already licenses. Implementation therefore involves the firm's existing systems and permissions, as well as the software on display.
04 / Donna needs a memory
PinSight turns the shared record toward the next conversation. Its PinScore ranks a contact's interest in a ticker using signals including readership, trading, CRM interactions and holdings. Behavioural profiles and inbox alerts help prioritize outreach. A score can provide a reason to investigate; it cannot tell a salesperson everything a client intends.
Donna, Datazoic's AI agent, extends that approach into morning briefs, ongoing activity feeds, conversational questions and personalized email openers. Users can describe what a feed should watch in ordinary language. Datazoic describes controls for material nonpublic information, information barriers and audit trails. These are product capabilities to examine against the firm's supervision requirements.
The practical lesson: test how quickly the record catches up with the relationship.
A September 2026 company essay makes the underlying argument explicit: AI inherits gaps when holdings, research engagement and interactions sit in systems updated on different schedules. Enrich addresses a quieter part of that problem through employment changes, bounced emails and bulk contact updates. A sophisticated answer about a person who has moved firms is still an answer about the wrong record.
05 / Industry knowledge, paid for by the founders
Founder and CEO Suresh Balaraman brings more than 20 years of buy-side and sell-side experience, according to Datazoic, with roles ranging from equities trader to chief administrative officer. Founded in 2017, the company describes itself as entirely founder-funded. Its stated culture emphasizes customer attention, independence and industry experience. It sells enterprise SaaS through a demo-led process, with onboarding and continuing support.
Datazoic reports more than 1,500 active users. It competes in a market that includes Singletrack's capital markets platform and, for banking relationships and deals, Intapp DealCloud. Its case rests on fitting sell-side work and connecting its economics. A buyer can borrow a simple test: follow one client from research read to meeting to trade. Check the timestamps, the evidence and the permissions. Then ask whether the person making the next call can see enough to make it a better one.