Earnix is built for large insurers and banks that want a single enterprise platform for pricing analytics, price optimisation and rating, run by an in-house pricing team. Swallow is built for insurers and MGAs that need a rating engine for live quoting, with models people can read, tests on every version and AI in the workflow. If optimising demand-based prices across a large personal lines book is the goal, Earnix deserves a close look. If the goal is getting a product live and keeping rate changes quick and controlled, Swallow is worth a look.
About Earnix
Earnix has worked with insurers and banks since 2001 and says it has customers in more than 35 countries. It calls itself "the first AI company purpose-built for insurance decisioning", offering cloud-based solutions for pricing, rating, underwriting and personalisation.
Its insurance pricing product is Price-It, which Earnix describes as "a dynamic pricing and rating solution" powered by data science, analytical modelling and AI. According to Earnix, it can produce prices and personalised offers in milliseconds, monitor live rates in real time and model the effect of a rate decision before it reaches the market. Alongside Price-It are an Enterprise Rating Engine, a Filing Accelerator for rate filing documentation, a Pricing Accelerator with dashboards and simulations, and Elevate Data for preparing data for modelling.
Earnix has announced integrations with Guidewire PolicyCenter, Sapiens IDITSuite and Verisk's ISO rating content. In a 2023 announcement with Guidewire, it cited price changes in under 30 minutes, and rate creation and deployment in under 72 hours.
In February 2025 Earnix launched Earnix Copilot, a generative AI assistant inside the platform. It offers best-practice guidance on building GLMs, explains how pricing changes reach production and can write Python code to automate data import. It runs on Amazon Bedrock.
Earnix doesn't publish its prices.
About Swallow
Swallow is a pricing platform and rating engine for insurers and MGAs. Each model is a JSON file of ordered steps: inputs, rate table lookups, calculations, exclusions, refers, excesses and endorsements. Teams build models on a visual canvas, from a prompt or an uploaded spreadsheet, or with an AI client such as Claude or ChatGPT over the MCP server. Every version keeps its own tests and moves from draft to approved to published. The same model serves quotes through a REST API, embedded forms, and voice and chat AI.
At a glance
| Swallow | Earnix | |
|---|---|---|
| What it is | Pricing platform and rating engine | Enterprise pricing, rating and decisioning platform |
| Typical buyer | Insurers and MGAs | Typically large insurers and banks with in-house pricing teams |
| Analytics and optimisation | Not the focus. Swallow puts rating structures designed elsewhere into production, with analytics on the quotes it serves | Core strength: modelling, simulation and price optimisation |
| Where models come from | Rating guides, spreadsheets, US rate filings or any modelling tool | Built by your team in the Earnix platform |
| Model format | Readable JSON of ordered steps; rate tables upload and download as CSV | Vendor specific |
| Testing | Tests saved on each version and run on a draft before approval; impact of changes shown visually | Impact modelling before release |
| Approvals and audit | Draft, approved, published; roles decide who approves; every quote records its version | Governed workflows described; detail not published |
| AI | AI builds models and tests from prompts and writes governance reports; MCP server for Claude, ChatGPT and Cursor | Earnix Copilot inside the platform; AI and machine learning in modelling |
| Distribution | REST API, embedded forms, voice and chat AI | Real-time rating; Guidewire, Sapiens and ISO ERC integrations |
| Commercial model | Talk to us | Not published |
Where they differ
How much of the pricing process each covers
Earnix spans a lot of ground: preparing data, building and validating models, optimising prices against demand and deploying rates. That breadth is the reason mature pricing functions at large carriers choose it. Swallow goes deep on a narrower stretch. It takes a rating structure that has already been designed, turns it into a production model, tests it, gets it approved and serves quotes from it, then handles every rate change after that.
Who builds and maintains the model
Enterprise platforms are usually run by the customer's own pricing team, often with an implementation partner for the first build. On Swallow, your team builds the model itself, in whichever way suits it: dragging steps onto the canvas, describing the product in a prompt, or having an AI client draft the JSON. If you'd like help, send us your rating guide, spreadsheet or filing and we'll talk you through getting it live.
Reading and checking a model
A Swallow model is plain configuration. Inputs have labels and descriptions, rate tables are rows, and every formula is written out, so an underwriter or auditor can follow it step by step. Each test fixes a full set of inputs to the result you expect, and you can run the whole suite on a draft before it's approved, so you see exactly which prices a change moves. For any single quote, the debug trace shows every input, lookup, formula and rule the engine worked through, and the quote records which version priced it. We cover why this matters in why pricing models should be human readable.
Where the AI sits
Earnix Copilot is an assistant for pricing teams inside Earnix, focused on guidance, code generation and scenario work. In Swallow, AI works on the production model and the process around it. It can generate a model from a prompt and a spreadsheet, generate tests, write version summaries and governance reports, and answer questions about your quote data. Through the MCP server, Claude, ChatGPT or Cursor can read the rules, draft a model, validate it and run its tests. No MCP tool creates, edits or publishes a project: the agent hands over the JSON, and a person uploads it to a draft, approves it and publishes it in the dashboard.
Getting prices to market
Earnix publishes integrations with Guidewire, Sapiens and ISO content. Swallow serves each published model through a documented REST API, embeddable quote forms, and voice and chat AI, all generated from the same model, so a rate change reaches every sales channel at once.
Cost
Neither vendor publishes pricing. Whichever you look at, ask for the full cost up to the first live quote, including implementation. For Swallow, talk to our team.
When Earnix is the better choice
- You're a large insurer with an established pricing team that wants analytics, optimisation and rating in one platform.
- Demand modelling and price optimisation sit at the centre of your strategy.
- You want a long-established vendor with a large international customer base.
- You run Guidewire or Sapiens and want the vendor's published connectors.
When Swallow is the better choice
- You're an MGA or insurer launching or migrating a product, and want it live without a large implementation project.
- Your rates already exist in a rating guide, spreadsheet or filing, or in a modelling tool you already use.
- You want models that people can read and audit, with tests on every version.
- You want AI clients to help build models under the same approval process as your team.
- You want one model to drive your API, quote forms and conversational channels.
Next steps
See a full model with its tests and release steps on the model building page, and how quotes are priced through the API. For the bigger picture, read our overview of Swallow vs insurance pricing platforms.
This comparison reflects publicly available information as of November 2026. Vendor offerings change and vary by customer, so check current details with each vendor.
