Upsolve AI

Paid

Embed AI-powered, no‑code analytics in your SaaS—live in a day

#AI#business intelligence#SaaS#no-code#dashboards#reports#applications#React#Vue#iFrame#insights#analytics#multi-tenant#role-based access#engineering#time-to-value

Inputs: textOutputs: text

Type

Saas

Founded

2023

Company

Upsolve AI

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About Upsolve AI

Upsolve AI is a platform designed to help data teams build and deploy analytics agents that provide trusted, context-aware answers to business questions. The platform emphasizes accuracy and reliability by encoding institutional context through three layers: structure (database tables and SQL patterns), meaning (semantic models with metrics and definitions), and context (from sources like Notion, Slack, and email). This allows users to ask questions in natural language and receive verified answers that include KPI verification, SQL pattern matching, and full data lineage. The platform claims to enable deployment of a working agent in as little as seven days, with accuracy that improves over time through ongoing conversations.

The platform appears to be targeted at SaaS teams and data teams who want to embed analytics capabilities into their own applications or provide self-service analytics to internal stakeholders. It supports integration with data warehouses (e.g., Postgres) and can connect to various external sources for context. The output is primarily text-based answers with supporting data, and the platform includes features for verifying answers against golden sources and tracking usage signals. Pricing is not publicly listed and requires contacting the company.

Key Features

No-code drag-and-drop dashboard and report builder

One-day setup and rapid deployment for embedded analytics

Embeddable components for React, Vue, or iFrame

AI-powered insights for trends, risks, and recommendations

Multi-source connectivity across databases, APIs, CRMs, and cloud storage

Automated and scheduled reporting with PDF/CSV outputs

Personalized user workspaces and end-user customization

Theme and design customization via CSS or built-in designer

Real-time analytics with live data and one-click refresh

User and usage analytics for product feedback and optimization

Pros & Cons

Pros

Focuses on answer accuracy and trust through verification and lineage
Claims rapid deployment (7 days to a working agent)
Encodes institutional context from multiple sources (Notion, Slack, email) for relevant answers
Supports natural language queries, reducing need for SQL expertise
Accuracy improves with use over time

Cons

Pricing is not publicly listed; requires contacting sales
Platform appears to be in early stages; long-term reliability should be verified
Integration with data sources may require initial setup and configuration
Dependence on external context sources (Notion, Slack) may introduce latency or access issues
Free tier or trial availability is not mentioned; should be verified

Best For

SaaS startups: Launch customer-facing dashboards in days to validate value and shorten sales cycles.Product managers: Ship no-code analytics experiences without diverting core engineering resources.Enterprises: Provide multi-tenant, role-based reporting that inherits existing RBAC and security models.Customer success teams: Automate scheduled PDF/CSV reports to keep customers informed without manual work.Data teams: Enable self-serve exploration via a data-aware AI agent that translates natural language to SQL.Fintech and regulated SaaS: Embed analytics that respect database-level permissions and audit requirements.Sales and solutions engineers: Create themed demo dashboards embedded in apps to showcase live insights.Operations leaders: Monitor real-time metrics and surface anomalies directly inside operational tools.Design and brand teams: White-label dashboards to match the product’s design system with CSS or the designer.Product analytics owners: Track dashboard usage to optimize features and improve end-user engagement.

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FAQ

What are credits, and how do they work?

Credits are Upsolve's universal unit for AI agent interactions. One credit equals the simplest possible AI response (like a clarification). A typical analytical question — where the agent writes SQL, fetches data, and summarizes the answer — uses around 5-10 credits. More complex queries with multiple joins, charts, or multi-step reasoning use more, but Upsolve caps at 20 credits per query. Credit usage is visible in real-time inside the platform.

What happens when my free credits run out?

The free tier includes 2,000 one-time credits — enough for roughly 200 analytical questions. Once used, you need to upgrade to a paid plan to continue using Upsolve. Your data connections, agent configurations, and context engineering work are all preserved, so upgrading is seamless.

What is Forward Deployed Engineering?

Forward Deployed Engineering is a service included in the Enterprise plan where Upsolve engineers work alongside your team to model the semantic layer, manage context, and ensure successful deployment. It is not available in lower tiers.