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AI for Data, Analytics and Research
Upmark Labs builds AI for founders, managers, analysts, and strategy, marketing, sales and procurement teams: agents that answer questions from your data, explain metric movements, write report commentary, and track competitors, markets, suppliers and regulation with cited sources. Each build has a fixed scope and a fixed price, shown before you buy. Order online or talk to an expert.
What problems do data and research AI solve?
Most businesses already hold the data and the public sources they need. The time goes into finding the answer, writing it up and noticing when something changes. The products in this area take on that repeat work and leave the decisions with your team.
If any of these sound familiar, this is the right area to start in:
- Managers wait for an analyst to answer questions that sit in data you already have.
- Recurring reports go out as tables of numbers, with no commentary on what moved and why.
- A key metric drops and nobody notices until the next review.
- Open-text survey answers sit unread because nobody has time to sort them.
- Competitor pricing and messaging changes reach the team late, or by chance.
- Supplier, market and regulatory research starts from a blank page every time.
What do we build for data and research teams?
Analytics products connect read-only, by default, to the data you already hold in tools such as Google Sheets, BigQuery, PostgreSQL, MySQL, Snowflake, Google Analytics 4 and Looker Studio. Every answer shows the query or source behind it, and scheduled summaries arrive by email or Slack.
Research products watch the web sources you choose on a set schedule. Findings are summarized with links to the original source and delivered by email, Slack or Notion, with change alerts when something moves.
- AI Data Analyst Agent: answers plain-language questions against your data and produces charts and summaries.
- AI KPI Monitor: watches your key metrics daily and explains unusual movements.
- AI Forecasting Assistant: forecasts demand, revenue or volume, with the assumptions explained.
- AI Report Narratives: writes the narrative commentary for your recurring reports.
- AI Survey Analysis: sorts open-text survey responses into themes and sentiment.
- AI Competitive Intelligence: maintains competitor profiles and battlecards from ongoing monitoring.
- AI Regulatory Research: tracks regulatory updates relevant to your business and summarizes them.
- AI Browser Automation Agent: completes repetitive browser tasks on sites without APIs, with approval steps.
How does a data or research project run?
Every product page shows the scope before you pay: the systems we connect, the sources we track, the testing we run and the rounds of changes you get. The price is fixed, and the fixed delivery time is shown on each product.
Third-party costs, such as AI model usage, hosting and web data or search services, are billed to your own accounts. You own the provider relationships, and nothing runs through us.
- Intake: you share read-only data access and your metric definitions, or the sources, competitors and questions a research brief must cover.
- Build: we configure the workflows, prompts and guardrails, and connect the agreed systems.
- Testing: analytics results are checked against your own historical data, and research products run trial report cycles that we review with you.
- Review: you check the results and request changes within the agreed rounds.
- Launch and support: you get an admin guide, a recorded handoff session and a period of post-launch support.
How do you choose the right data or research product?
Start with the question your team asks most often, then pick the product that answers it. If the data itself is messy, AI Data Cleaning standardizes it with a documented rule set, so start there before any analytics product.
Industry editions adapt a product to your sector. The AI Data Analyst Agent comes in editions for Ecommerce & D2C, SaaS, Retail, Logistics, Manufacturing, and Hotels & Hospitality. AI Price Monitoring comes in editions for Ecommerce & D2C, Retail, Travel & Tourism, Automotive, and Hotels & Hospitality.
Migrating historical data and writing source content you do not provide sit outside the standard scope. If nothing listed fits, talk to an expert and we will scope a custom build with you.
- People ask questions of data and wait for answers: the AI Data Analyst Agent. If you already run dashboards, the AI BI Assistant explains them; analysts who write queries can use the AI SQL Assistant.
- You want one conversational view of your key metrics: the AI Business Intelligence Dashboard.
- Problems surface too late: the AI KPI Monitor for daily metric checks, or AI Anomaly Detection for transactions, traffic or operations data.
- You need to know what customers think and who they are: AI Survey Analysis for open-text feedback, AI Customer Insights for segment-level views across customer data sources.
- You track the outside world: the AI Competitor Website Monitor for page, pricing and messaging changes, AI Market Research Agent for structured market reports, or AI Supplier Research and AI Procurement Research for buying decisions.
- You want one regular view across all of it: AI Market Intelligence combines market, competitor and customer signals into a monthly intelligence report.
Data, Analytics and Research in the Store
AI Competitor Website Monitor
Tracks competitors' pages, pricing and messaging changes.
AI Procurement Research
Researches vendors, pricing benchmarks and contract norms.
AI Regulatory Research
Tracks regulatory updates relevant to your business and summarizes them.
AI News Intelligence
Delivers a curated news digest on your industry and accounts.
AI Competitive Intelligence
Maintains competitor profiles and battlecards from ongoing monitoring.
Browse the Store by category: Data & Analytics Research & Intelligence
Questions buyers ask
Can the AI change or delete data in our systems?
Not the analytics products. They connect to your data sources read-only by default, so they can query and summarize your data but cannot edit it, and every answer shows the query or source it used. The action products work differently: the AI Browser Automation Agent and the AI Web Task Agent have read and write access to the systems agreed in scope, and you name the approver for any action that needs a person.
How do we know the answers and forecasts are right?
You can check them. Analytics answers show the query or source behind them, and the AI Forecasting Assistant explains the assumptions behind each forecast. Before launch, results are checked against your own historical data and you receive a test report. Research findings link to the original source. No build guarantees a business result, so your team still reviews the numbers before acting on them.
Which data sources and tools do these builds connect to?
Analytics products typically connect to Google Sheets, BigQuery, PostgreSQL, MySQL, Snowflake, Google Analytics 4 and Looker Studio, and deliver to email, Slack or a web dashboard. Research products work from web sources and RSS feeds, can connect to Google Sheets, and deliver to email, Slack or Notion. Each product page lists exactly which systems are in scope, and extra systems are available as add-ons.
What do we need to provide before the build starts?
For analytics products: read-only access to each data source, your definitions of the key metrics, the questions the business asks most, enough historical data to check results against, and who receives the reports. For research products: the sources, competitors or topics to track, the questions each brief must answer, and access to the delivery channel. Every build also needs one person who approves decisions. Late intake items move the delivery date.
Can AI Regulatory Research tell us whether we are compliant?
No. AI Regulatory Research tracks regulatory updates relevant to your business, summarizes them and links each finding to its original source, so your team starts from a short summary instead of the raw text. Whether a change applies to you, and what to do about it, stays a decision for qualified people such as your legal or compliance advisers. Supplier and procurement research works the same way: it informs the choice, and your team makes it.
What does a data or research build cost to run after launch?
The build price is paid once. Running costs are billed by the providers to your own accounts: mainly AI model usage and hosting or a scheduler for analytics products, and AI usage plus web data or search services for research products. Each product page shows a running cost estimate for that build. An optional maintenance plan, billed monthly, covers changes after the post-launch support period ends.
Start with the question your team asks every week.
Find the build that answers it in the Store, or talk to an expert about which data or research product to order first.