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Settle Up VS Knowi

Compare Settle Up VS Knowi and see what are their differences

Settle Up

SETTLE UP is an indispensable app for friends and flatmates who need to keep track of shared bills...

Rating
0 reviews
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Alternatives Is it good?
Knowi

Knowi is an agentic analytics platform. AI agents work inside the data layer to query SQL, NoSQL and APIs directly, join across sources without ETL, and build dashboards teams can use or embed in their own product.

Rating
0 reviews
Pricing
Free Free trial
Promote on VibeVoted
Alternatives Is it good?
Grapple
Do-It-Yourself Data Analytics & Business Intelligence, Powered by AI sponsored

Which is more popular?

Based on our record, Settle Up seems to be more popular. It has been mentioned 1 time since March 2021.

social mentions
1 vs 0
Personal Finance popularity
100% vs 0%
alternatives listed
163 vs 62

Base details

Website, pricing, platforms and company facts side by side.

Settle Up
Knowi
Website settleup.io knowi.com
Pricing —
Free Free trial Official pricing
Company — Startup from the United States · 20 - 49 employees · 2015
Listed in
Personal Finance Expense Tracking Bill-Splitting Apps Business Intelligence +1
Analytics Product Analytics IoT Platform Business Intelligence Embedded Analytics Data Visualization Reporting & Dashboard AI Agents Agentic Analytics Analytics Dashboard Marketing Analytics +8

About Settle Up and Knowi

In their own words, as submitted to SaaSHub.

Settle Up
Knowi

No description of Settle Up yet.

Knowi is the Agentic Analytics Platform. It unifies data from anywhere, adds a governed semantic layer, and deploys AI agents that analyze, monitor, and act on live business data. Traditional BI tools bolt AI onto dashboards. Knowi was built AI-first. The semantic layer defines your metrics,...

Read more about Knowi

Features and specs

What each product offers, as listed by its team.

Settle Up 5 features
Knowi 10 features
  • User-Friendly Interface
    Settle Up features an intuitive and easy-to-navigate interface, making it simple for users of all technical abilities to manage expenses and track payments among friends, family, or colleagues.
  • Multi-Platform Availability
    The app is available on multiple platforms, including iOS, Android, and web, allowing users to access and update their accounts from various devices seamlessly.
  • Currency Support
    Settle Up supports multiple currencies, which is ideal for travelers or groups of friends and family in different countries needing to manage expenses accurately.
  • Offline Functionality
    The app allows users to add and edit transactions offline, syncing changes once internet connectivity is restored, enabling expense management on-the-go without interruption.
  • Group Expense Tracking
    Settle Up facilitates the tracking of shared expenses by allowing users to create groups, making it easier to split bills and settle debts among group members.

Possible disadvantages

  • Limited Financial Tools
    The app mainly focuses on tracking expenses and lacks more comprehensive financial tools, such as budget planning or financial goal setting, which might be desired by users looking for more robust financial management features.
  • Ads in Free Version
    The free version of Settle Up includes advertisements, which might be distracting or annoying for users, though there is an option to upgrade to a paid version to remove ads.
  • Dependency on Group Members
    The effectiveness of Settle Up largely depends on the active participation of all group members involved in the expenses, which can be a drawback if not everyone is keeping their entries up to date.
  • Privacy Concerns
    Sharing financial data, even among friends and family, raises privacy concerns for some users who might prefer not to have their spending habits monitored by others, regardless of the app's security measures.
  • Data Sync Delays
    Users may occasionally experience delays in data syncing across devices, leading to temporary discrepancies in expense tracking, though this is generally resolved once syncing is completed.
  • Agents Inside the Data Layer
    AI agents connect to schemas and the query engine directly rather than sitting on top of finished dashboards, so they build queries, widgets and dashboards instead of only answering questions about ones that already exist.
  • Native NoSQL Analytics
    Query MongoDB and Elasticsearch in their own query language, including nested documents and arrays, without a BI connector or a separate flattening step.
  • Cross-Source Joins Without ETL
    Blend MongoDB, PostgreSQL, Snowflake, Databricks SQL, Trino, Salesforce and REST APIs in a single query, without first moving the data into a warehouse.
  • Semantic Layer as a Dataset Service
    Curated datasets, governed business definitions and a shared glossary the data team controls, so plain-English questions resolve against approved metrics rather than raw tables.
  • Wide Range of Integrations
    The platform connects to relational databases, NoSQL stores, cloud warehouses, SaaS APIs and files, including MongoDB, Elasticsearch, PostgreSQL, MySQL, Snowflake, Databricks SQL, Trino, BigQuery, Redshift, Salesforce and REST endpoints.
  • Real-Time Insights
    Knowi provides real-time data processing and visualization, which enables businesses to access up-to-date insights for timely decision-making.
  • Alerts and Scheduled Reporting
    Threshold and anomaly alerts routed to Slack, email or webhooks, plus scheduled PDF and CSV delivery.
  • MCP Server for AI Assistants
    A Model Context Protocol server so assistants such as Claude can query data, build widgets and create dashboards through Knowi's governed layer.
  • Flexible Deployment
    Run on Knowi Cloud, inside your own VPC, or fully on-premise.
  • No-Code Data Analytics
    Knowi offers a no-code platform that allows users to perform data analytics tasks without needing in-depth programming skills, making it accessible to data-driven teams.

Videos

Walkthroughs and reviews on video.

Settle Up 3 videos + Add
Knowi 1 video + Add

Settle Up - hisab rakhna hua aasan

More videos

  • - Settle Up - iOS and Android app for organizing group expenses
  • - Settle UP - mobile APP for shared expenses

Knowi: End-to-End AI Analytics Platform - Architecture Overview

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
Settle Up
Knowi
100% 100%
Personal Finance
0% 0%
0% 0%
Analytics
100% 100%
100% 100%
Expense Tracking
0% 0%
0% 0%
IoT Platform
100% 100%

Questions & Answers

As answered by people managing Settle Up and Knowi.

Who are some of the biggest customers of your product?

Knowi's answer:

Verizon Telstra Everbridge ConvergeOne NJM Insurance Volante Systems intlx Solutions Alteas Health Hometime Tata

What makes your product unique?

Knowi's answer:

Knowi runs AI agents inside the data layer rather than on top of finished dashboards. The agents reach schemas and the query engine directly, which means they can build queries, widgets and dashboards, not just answer questions about ones that already exist.

That architecture comes from what Knowi was built to do: query data where it already lives. It speaks MongoDB and Elasticsearch in their own query language, including nested documents and arrays, and it joins across MongoDB, PostgreSQL, Snowflake, Databricks SQL, Trino, Salesforce and REST APIs in a single query without first moving anything into a warehouse.

Knowi also runs its own AI by default, with OpenAI and Claude available as optional integrations rather than requirements, and it deploys to cloud, your own VPC, on-premises via Docker or Kubernetes, or air-gapped.

Why should a person choose your product over its competitors?

Knowi's answer:

Three practical reasons.

Your data does not have to be relational first. Most BI tools need a warehouse and an ETL pipeline before you see a chart, which means unstructured, nested and API data either gets flattened or gets left out. Knowi queries those sources natively, so the modelling work you would normally do up front becomes optional.

The AI is part of the query path, not a chat box on the side. Many platforms added a copilot that describes existing dashboards. Knowi's agents have access to the schema and the query engine, so they can create new datasets, widgets and dashboards from a question.

You control where it runs and which model touches your data. Knowi AI is the default, third-party models are optional, and deployment can be Knowi Cloud, your own VPC, on-premises, or air-gapped. Knowi is SOC 2 Type II certified, GDPR compliant, and offers a HIPAA BAA.

How would you describe the primary audience of your product?

Knowi's answer:

Data, engineering and product teams at mid-market and enterprise companies whose data is spread across more than one kind of system: NoSQL alongside SQL, warehouses alongside SaaS APIs and documents.

Two buying patterns show up most often. Internal analytics teams who need governed self-service across sources without building a pipeline for every question. And product teams who need customer-facing, multi-tenant analytics embedded inside their own application with row-level access control.

By industry, the customer base skews to telecom, healthcare, manufacturing, SaaS and adtech, proptech and e-commerce. Knowi is sold through a sales team and priced per deployment rather than by public self-serve tier.

What's the story behind your product?

Knowi's answer:

Knowi was founded in 2014, at the point where a lot of production data had stopped being relational. Teams were running MongoDB and Elasticsearch, and the BI tools of the day all assumed a star schema in a warehouse. Getting a dashboard meant building a pipeline first, and anything nested or semi-structured got flattened or dropped along the way.

Knowi was built the other way round: connect to the source, query it in its own language, and join across sources at query time instead of moving the data. Cross-source joins, post-query transformation and a dataset layer that data teams could govern followed from that starting point, and embedded analytics came from customers who wanted to give the same views to their own users.

The AI work is a continuation rather than a pivot. Because Knowi already owned the query path across every connected source, AI agents could be placed inside the data layer with access to schemas and the query engine, instead of being bolted onto a finished dashboard.

User comments

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Reviews and articles

External articles and on-site reviews we used to compare the two products.

Settle Up no reviews yet
Knowi no reviews yet

We have no reviews of Knowi yet. Be the first one to post

Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

Settle Up 1 mention
Knowi 0 mentions

Tracking Knowi since Mar 2021.

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