Structured products. AI-native.
From client brief to review-ready term sheet.
OpenArrow takes structured products from brief to price, stress, document and review in under 60 seconds, powered by one deterministic engine. Work in chat, through your AI assistant, or via API.
Desk run
3Y NIFTY capital-protected note
- 09:12
Brief · RM, private wealth
“3 years on NIFTY, full capital protection, best participation you can get. ₹10L ticket.”
- 09:12
Priced · arrowquant
NIFTY vol surface, latest close · A1+ funding 9.50%
Quote - 09:13
Stressed · arrowquant
Spot ±20% × vol ±5 pts · investor SRI 1 of 7
- 09:13
Documented · arrowquant
KID and term sheet generated
KID.pdf - 09:13
Logged · usage dashboard
Three engine calls recorded against key oa_k…7f2: tool, status, duration and time, linked to the chat turn.
NIFTY · Gold
Index and gold underlyings
< 60 s
Brief to review-ready KID
10
Payoff families
17
Templates on the Structures shelf
61
MCP tools for your AI assistant
The workflow
Five steps a desk already takes. Minus the spreadsheets between them.
Each step hands the next one the same numbers. The quote, the stress grid and the KID come from one engine run, so they agree.
01 · Brief
Start from the client’s words.
An RM or PM describes the need in plain language: in OpenArrow chat, inside the AI assistant the team already uses, or through the API. The agent maps it to a payoff family and asks for what is missing.
02 · Price
Priced on a calibrated surface, not a flat vol.
Smile-consistent pricing off the daily-calibrated vol surface, on the issuer’s own funding curve. Change the ask, protection, cap or barrier, and the terms reprice in seconds.
About the arrowquant engine03 · Stress
Know what moves it before the client asks.
Two views, kept apart: the issuer’s hedge Greeks and spot × vol stress grid, and the investor’s outcome at maturity, with worst case, VaR, expected shortfall and the summary risk indicator.
Issuer MtM · spot × vol
Investor · at maturity
Summary risk indicator
Worst case
₹0100% protected at maturity, subject to issuer credit.
04 · Document
The KID writes itself. You still read it.
A regulation-style key information document and term sheet, with risk indicator, performance scenarios, cost breakdown and payoff profile, built from the same run that priced the note. Ready for internal review, not for skipping it.
Key information document
3Y NIFTY Participation Note
Performance scenarios
Indicative term sheet
Terms & costs
05 · Review
Review with a trail behind it.
Every engine call is logged against the access key that made it: which tool ran, when, whether it succeeded, and the conversation it came from. Product heads review from there. Revoke a key and it stops working at once.
Who we serve
Same engine. Different desks, different Tuesdays.
Wealth desks & private banks
Illustrate the product before the client call ends.
brief → price → KID into the client pack
Read moreIssuers & treasury
Design the note on your own funding curve.
NBFCs and corporates issuing market-linked debt
Read moreFund managers & quants
Daily derivatives monitoring, without the in-house tooling.
positioning · GEX · smile vol regime, every morning
Read moreFintech platforms & agent builders
Put structuring inside your own product.
MCP or API one integration
Read moreHow it works
Work where you already work. One engine underneath.
Chat, your AI assistant, the API and the Structures shelf all call arrowquant. A quote in chat matches the shelf and the KID to the paisa.
OpenArrow chat
Conversational structuring
Your AI assistant
61 tools over MCP
API
For platforms and agents
Structures shelf
17 ready templates
Engine
arrowquant
Vectorised end-to-end, deterministic
Daily-calibrated vol surfaces
Forward, discount and funding curves
Monte Carlo and closed form
Quote
Terms, fair value, costs
Risk
Greeks, stress grid, risk indicator
KID & term sheet
PDF, review-ready
Bespoke payoffs
Payoff graphs priced on the same paths
Getting started
Your first 7 days.
Day 1
Account, keys, connected
Keys are provisioned from the dashboard and your AI assistant links in minutes. Nothing to install on your side.
Day 2
Price the shelf
Work through the 17 templates and the structures your desk already sells, on today’s surface.
Days 3–6
Pilot on your book
Run live briefs through your own review process, side by side with how you do it today.
Day 7
Decide on evidence
The usage dashboard shows what was priced and documented, and by whom. Then you decide.
Education
Teach structuring the way desks do it.
Colleges and universities can license OpenArrow for classroom teaching, labs and research, starting this academic year.
Students design, price and document structured products by talking to an AI agent, working with calibrated market data and the same pricing engine that powers OpenArrow's production platform.
Classroom
Build structured products such as reverse convertibles in conversation, then examine the term sheet the engine produces. Every number is engine-computed, not LLM-generated.
Labs
Explore volatility surfaces, Greeks, scenario analysis and key information documents through hands-on exercises on daily-calibrated data. Change assumptions, rebuild, reproduce.
Research
Programmatic access to the pricing engine and historical volatility surfaces for derivatives, fintech and AI research, with usage tracked by seat for labs and research groups.
Controls
The model talks. The engine computes.
Language models are good at understanding a brief and bad at arithmetic. So they never produce a number.
Deterministic
Same inputs, same numbers
Reproducible pricing on a recorded surface snapshot.
Engine-computed
No generated figures
Every figure in a quote, KID or term sheet comes from arrowquant.
Governed
Per-key audit and revocation
Usage metered and logged per seat, revocable at once.
Bring your own engine. Bring your own data.
Run your validated models and keep proprietary data in-house, behind OpenArrow's workflow and agent layer. Scoped per deployment on enterprise plans.
Pricing
Tailored to your team.
Every desk is different. Tell us about your workflow and we'll put together the right plan, free evaluation included.
Questions desks ask first.
All FAQsDoes the language model produce any of the numbers?+
No. The model interprets the brief and calls the engine. Every price, Greek, scenario and cost is returned by arrowquant and passed through unchanged.
Which underlyings and payoffs are supported?+
NIFTY and gold today, with daily-calibrated vol surfaces. Ten payoff families cover capital-protected and yield-enhancement notes, and the Structures shelf ships 17 ready templates, including bespoke Indian notes described as payoff graphs. Additional underlyings are added on client demand.
Can we use our own pricing models or data?+
Yes, on an enterprise plan. Running your validated models and keeping proprietary data in-house behind the workflow layer is scoped as part of a dedicated deployment. Tell us what you run today and we will map it.
Is the KID ready to hand to a client?+
It is ready for internal review. The document carries the risk indicator, performance scenarios and cost breakdown from the same engine run, but final terms and client-facing documents always come from the issuing institution.
Which AI assistants can connect?+
Any workspace that supports the Model Context Protocol, Claude, Cursor and VS Code among them, through a one-time connection that takes a few minutes. OpenArrow chat needs no setup at all.
Put one product through the workflow.
Bring a real brief from your desk. We'll run it end to end in 60 seconds, brief to review-ready KID.