AI for investing and trading apps
Research with sources, and orders the investor confirms, in one conversation.
For investing, trading and market data products. Answers that cite the filing or story behind them, agents that prepare orders from the investor's profile, and paid data gated on the server.
Built for: Retail investing and trading apps, market data and research products, prediction market tools.
Already built or tried AI? Get it scored with the AI Scorecard.
keelstone.example/research
Keelstone Invest · Citely
DemoStep 1 of 5
Illustrative demo on a fictional firm. Not client work.
Where these products get stuck
What gets in the way, and how we handle it.
- 01
Answers without sources
Cited from your own data
Answers come from your data first and cite the filing, story or post behind them.
- 02
Too many panels
One conversation
Specialist agents behind one chat, from an idea to a prepared order.
- 03
Paid data leaking to free plans
Gated on the server
Every request for paid data is checked on the server for the user's plan.
AI inside your product
The modules that fit this kind of platform.
Each one is shown on a fictional firm. It is built into your codebase and ships under your name, on an engine we license to you.
What it connects to: Your market data providers, filings, news and social sources, broker integration, sign in and billing. Sprints use sample data and a broker sandbox.
Citelyby Datics AI
Cited AI research answers over market data
Investors ask about a company or the market and get an answer that cites its sources.
Fits: Investing and trading apps, market data and research products, wealth platforms
Tradelyby Datics AI
AI investing agents that prepare orders investors confirm
From research to a prepared order in one conversation, and the investor confirms it.
Fits: Investing and trading apps, brokerage front ends
Proof
What we have built that this rests on.
57 featured AI case studies: AI products and AI built into live products, each written up on our Work page.
Cosmic AI
Investing apps · Agents to orders
Retail investors go from research to a confirmed order in one conversation
Investors juggled data, news and a separate broker. Now agents research and prepare each trade in chat, and nothing is placed until they confirm.
Cosmic AI
Investing apps · Cited research
Investors get answers that cite the filing, news story or post behind them
Filings, news, social posts and market data sat on different sites. Now one chat answers from all of them and cites the source behind each answer.
Peret
Trading analytics · Prediction markets
Traders see AI forecast edges in an inherited app, finished without a rebuild
Peret had another developer's half finished build. We proved what worked, fixed the rest for beta and delivered its prediction network.
Cosmic AI
Cosmic AI · Plain English analytics
Business teams ask their databases plain English questions without data leaving their network
Answers used to wait on an analyst. Now teams ask in plain English, and the copilot answers inside their network with the SQL shown.
How it works
Three ways to start, each at a fixed price.
Most investing apps start with Citely in a Build Sprint: one source type indexed and cited answers in the chat.
Fintech Platform Product Review · 30 minutes, no chargeStart here. We look at your platform with you, agree the outcome you want for your users, and tell you which of the three below fits.
Book a 30-minute Product ReviewNo AI yet, and a module fits
Build Sprint
$10,000 fixed3 weeks
Pick it when: One of our modules delivers the outcome you want.
- One user outcome (2 to 3 related capabilities) working in your staging, behind a feature flag
- Pull requests to your repo, built on sample deals, documents and synthetic accounts
- Quality and safety evals, the cost per user and a packaging recommendation
- A fixed-price quote for production
Something new, or a plan first
Planning Sprint
$5,000 fixed2 weeks
Pick it when: You need something our modules do not cover, or want a plan before you build.
- Where AI fits across your platform, including beyond our modules
- A prioritized capability map, with what each one depends on
- A readiness review of your architecture, data, integrations and permissions
- A fixed-price quote to build it and take it to production
AI already built or tried
AI Scorecard
$5,000 fixed2 weeks
Pick it when: You have already built or tried an AI feature in your platform, live or not.
- One AI feature you have built, tested in staging on 50 of your own cases, with names and account details removed
- Tests for invented numbers, missing sources, another user's data and prompt injection
- Cost per user and a packaging recommendation
- A scorecard, ranked fixes, draft security answers and a fixed quote
Not a compliance audit or certification.
How the AI Scorecard worksProduction, at a fixed quote
We take what your Sprint built or planned live for your users, by pull request, with no standing production access. It typically includes load testing at your peak and a spend cap per firm. Your Sprint or Scorecard fee counts toward it.
After go-live, optional support
The product is finished and yours to run. If you want us to stay on: a named lead engineer, a monthly quality and cost report, testing before any model change, and more capabilities, each at its own fixed quote.
Stop after any Sprint and keep what you got.
How a Build Sprint runs
- In the setup week we map your core system, data and roles and agree what the Sprint touches.
- We follow your coding standards, tests and CI; your engineers review and merge every pull request.
- Half at signature, half when the Sprint Pack is delivered.
- Your time: about 2 to 3 hours a week from a product owner, plus an engineer to review pull requests.
Product improvements you can measure
What we agree to measure: quality and cost on test sets in the Build Sprint, adoption and outcomes once it is in production, so the decision to go further is made on evidence.
Answers users can check
Share of answers with a cited source
Users who act
Conversations that end in a prepared order
Predictable cost
AI cost per user, by plan
We set the success measures with you in the setup week.
Built for regulated platforms
Controls your customers' security reviews ask about.
Each control is a design fact about how the module is built and how we work, not a compliance claim.
Beside your core
Services that reach your system of record only through its APIs and the roles it already has.
Sample data in Sprints
Sprint work uses sample deals, documents and synthetic accounts, and ships as pull requests to your repo.
People decide
Orders, deal values, interest and KYC go ahead only when a person confirms them.
We work within your SEC, FINRA, AML and KYC, and privacy requirements. Compliance depends on the complete product, contracts, policies and operating environment; Datics does not present software engineering alone as legal certification, and nothing a module shows is investment advice on its own.
How we handle financial data and decisionsQuestions we hear on the first call
Straight answers before you book.
Can the AI tell investors what to buy?
No. Agents explain what the sources say and prepare the order the investor asks for. Whether your platform may make recommendations is your compliance team's call, and the investor confirms every order.
How do you keep AI costs in line with plans?
Each plan sets which agents a user can reach, refresh cadences are set around the AI provider's limits, and we log usage and cost per user in what we build.
Other fintech platforms we build for
See it on your own platform.
Bring one product, workflow or AI feature. In 30 minutes we tell you which of the three ways to start fits, what it would cost to serve per user and what your compliance team will ask.
Calls run in US Central time. No generic AI presentation: we discuss your product, users and production constraints.