Gigasheet
Gigasheet is a US healthcare price intelligence platform turning public payer and hospital rate disclosures into searchable benchmarks. It covers 150 billion+ negotiated rates for providers, payers, self-insured employers and MedTech teams, via spreadsheet, API or AI agent.
What is Gigasheet?
Gigasheet is a healthcare price intelligence platform published by Gigasheet, Inc. from Leesburg, Virginia. The company started in 2020 as a browser spreadsheet for files too big for Excel, and has since pointed that engine at a single market: US healthcare price transparency. Its raw material is public data that federal rules push onto the open web, namely payer Transparency in Coverage files, hospital price transparency disclosures and the CMS NPPES provider registry. Gigasheet says it has processed more than 150 billion negotiated rates and counts over 150,000 users.
Four products sit on top of that corpus, alongside bulk data licensing. The Price Transparency Explorer searches negotiated rates nationally, with precomputed benchmarks and Medicare comparisons. Two proprietary measures structure the analysis: the Smart Rate, a heuristic that strips outliers and rates that are not comparable, and the Provider Rate Score, which places a rate against the benchmarks of its own market. The MRF Viewer opens and flattens the machine-readable files themselves. A REST analytics API returns aggregations already enriched with benchmarks, and an AI agent answers in natural language through MCP, ChatGPT, Claude or the in-app chat, while the Sheet Assistant, backed by OpenAI, turns plain English into filters and formulas.
The interface stays a spreadsheet: filters, sorts, aggregations, pivots and cross-file lookups, with no query language and no code. The publisher's recurring promise is traceability, since every benchmark unrolls down to the source record it came from, which matters when a number is about to be used in a payer negotiation.
What Gigasheet does not claim is just as telling. Public price data can be incomplete, outdated or misattributed, and the company says so itself, running a public procedure for providers to request a review of their information. Rate scores are statistical comparisons of published prices, not judgements about credentials, clinical quality or outcomes. The founders come from national security, cybersecurity and big-data engineering at Google and in banking. Gigasheet is a registered trademark and the site claims patents.
What it does
- Compare negotiated rates across providers, payers, plans, procedure codes, geographies, networks and sites of care
- Position any rate against its market with the Provider Rate Score, from Bottom of Market to Top of Market
- Open and flatten machine-readable JSON or CSV files of up to one billion rows
- Ask the AI agent a question in plain language and get a market intelligence report with its supporting data
- Run aggregations and statistics through the analytics API without moving the data
- Blend public rates with your own claims, provider rosters or business rules
- Drill from a benchmark down to the source rate records, then export any filtered subset to CSV
When to use Gigasheet / When not to
A quick filter to help you decide if Gigasheet is the right fit.
When to use Gigasheet
- Hospital and provider contracting teams building evidence for payer rate negotiations
- Payer network development and pricing strategists benchmarking their own contracted rates
- Self-insured employers and benefits brokers comparing plans, networks and market rates
- MedTech and life sciences teams working on market access, forecasting and reimbursement strategy
- Data teams that need to open machine-readable files far too large for a desktop spreadsheet
When not to use Gigasheet
- Patients looking for a personal cost estimate: published rates are not quotes and ignore deductibles or out-of-pocket shares
- Analysts who need claims or executed contract data, which the publisher states this does not replace
- Teams working outside the United States, since coverage stops at NPPES, Transparency in Coverage and Hospital Price Transparency sources
- Buyers looking for clinical quality or credentialing signals, which rate scores deliberately do not measure
- Organizations under strict GDPR obligations, as the publisher declares itself not yet fully GDPR compliant
How to use Gigasheet
A typical end-to-end flow, from setup to results.
- Create a free account on the Gigasheet app, or sign in with Google, Microsoft or GitHub SSO
- Upload a file through +New > File Upload, from your device, Google Drive, Dropbox, OneDrive or AWS; ZIP archives are unpacked automatically
- Let Gigasheet parse and flatten the file: each tab of a workbook becomes its own file inside a folder
- Open the file from your library, where it loads as a spreadsheet in a new browser tab
- Clean, filter, group, aggregate and pivot; combine up to 100 files at once and run lookups between them
- Ask the Sheet Assistant in plain language to filter, group, chart or write a formula for you
- In the Price Transparency Explorer, search by provider, payer, billing code or market, then drill down to the source rate records
- Connect the REST API with a key generated from support, or the MCP endpoint, to plug in an LLM or a BI tool
- Export the filtered subset to CSV, or feed the sheet straight into Tableau or Power BI
- For the healthcare offers, go through a pricing request or a scheduled demo
Pros & Cons
Pros
- Scale: more than 150 billion negotiated rates queryable with no ETL work beforehand
- Traceability: every benchmark unrolls down to the published source record
- No code and no query language needed for day-to-day analysis
- Three routes into the same data: web interface, REST API, and AI agent through MCP
- SOC 2 Type 2 under continuous third-party audit and NIST 800-171, with AES 256 encryption at rest and TLS in transit
- The publisher states it does not train AI models on customer data
- A permanent free account lets you test the spreadsheet engine before any commitment
Cons
- Not fully GDPR compliant by the publisher's own admission, with no DPA and no subprocessor list published
- Opaque pricing on the healthcare side: the four healthcare segments all sit behind a Request pricing form
- The self-service price grid lives on a separate subdomain and is absent from the pricing page itself
- Premium Individual excludes JSON and MRF files, which is precisely the material the current business is built on
- High entry ticket for machine-readable files at USD 295 per user per month on annual billing, with an annual commitment required
- No refunds, even partial, and stored data can be removed at Gigasheet's discretion on the free tier and after cancellation
- US-only data coverage, no mobile app, and support routed mainly through a Freshdesk help center
Pricing & Plans
Gigasheet operates on a freemium basis. A permanent free account is available, and no time-limited free trial is advertised. The lowest published paid entry point is Premium Individual at USD 75 per user per month on annual billing, or USD 95 per user per month billed monthly. The MRF Viewer plan starts at USD 295 per user per month on annual billing, that is USD 3,540 per year, with an annual commitment. The Price Transparency Explorer and the four healthcare segments carry no published price and require a pricing request. The terms of use provide for no refunds, even partial.
- free account with file upload and analysis
- stored data removable at Gigasheet's discretion
- 1 user
- 25 million rows per sheet
- 25 to 75 GB storage
- advanced filters and exports
- up to 100 files combined
- 25 API calls per day
- secure sharing
- BI connection
- 1 user
- 1 billion rows per sheet
- 500 GB storage
- JSON and MRF support
- all Premium Individual capabilities
- annual commitment. From USD 295 per user per month on annual billing
- 5 users
- 2 billion rows per sheet
- 500 GB or more of storage
- verified and cleaned price transparency data
- competitive intelligence and benchmarking reports
- full payer and hospital market coverage
- shared workspace
- warehouse and database integrations
- tiers named in the terms of use that require contacting sales
- with custom SSO on Enterprise
- licensing of complete datasets covering rates
- provider resolution and provider contacts
- by appointment
Data, GDPR & hosting
A consolidated view of how Gigasheet handles your data.
GDPR overview
Gigasheet's own Security page states plainly that, while it meets many GDPR standards, the company is not yet fully GDPR compliant and is working toward it. That admission sets the level: partial alignment, no compliance claim. No EU representative under Article 27 is named anywhere on the site, no data processing agreement is offered and no subprocessor list is published, even though AWS, OpenAI and Google appear individually across the pages. The terms confirm that personal data may be transferred to and processed in the United States, and the company undertakes to cooperate with local supervisory authorities on complaints about those transfers. Privacy questions go to privacy@gigasheet.com, policy questions to legal@gigasheet.com, and data deletion is handled on request through the support site. The retrieved privacy policy shows no visible effective date, although its own text says one appears at the top.
Who owns the data?
Users keep the intellectual property rights in everything they upload, and Gigasheet states it claims no ownership of user content. In exchange, the terms grant the company a worldwide, royalty-free, irrevocable, transferable and sublicensable license to use, copy, store, modify and display that content in order to deliver and improve the service. A separate clause goes further: public data uploaded by users, such as CC0 material, government files or Transparency in Coverage disclosures, carries a perpetual license letting Gigasheet aggregate, distribute and commercialize it. On Organization accounts, the company may presume all content belongs to the organization. Users can delete content, with the caveat that some copies may not be fully removed.
Reuse rights
Gigasheet limits its use of uploaded content to providing, maintaining and improving the service, plus purposes compatible with its privacy policy, and states that it neither sells nor shares user data except at the user's request or where the law compels it. Enrichment queries send metadata and anonymized information to partner data providers; non-anonymized data is not shared. The Sheet Assistant passes prompts and file metadata to OpenAI, meaning column names, types and a small sample of rows, but never identity, email or company name, and the full dataset only with explicit consent. The company states it does not use customer data for AI training and never sends personally identifiable information to third-party AI models. Public healthcare data it collects from NPPES, Transparency in Coverage and Hospital Price Transparency is normalized, enriched and commercialized as benchmarks and comparisons, and non-identifying aggregates may be shared with third parties. Users are free to filter, analyze and export their own results to CSV without asking permission, and to feed them into BI tools or their own systems through the API. In a merger or sale, collected information counts among the transferable assets, with prior notice to users.
Data retention & training
Hosting summary
All customer data is stored in Amazon Web Services data centers. Gigasheet says its AWS servers are reachable only through a VPN and are kept separate from employee workstations. No specific AWS region is named, so the precise location is undisclosed, but the terms of use state that personal data may be transferred to and processed in the United States. The publisher cites AWS certifications, including SOC 3, PCI DSS Level 1, ITAR, FIPS 140-2, ISO 27001, ISO 27017, ISO 27018 and ISO 9001, alongside its own SOC 2 Type 2 and NIST 800-171 posture. Data is encrypted with AES 256 at rest and travels over HTTPS on SSL/TLS; passwords are hashed and salted, and DNSSEC is in place. Public DNS resolves behind Cloudflare on an anycast address. The gaps are worth noting: no region-level commitment, no data processing agreement and no published subprocessor list, which leaves a European buyer without any contractual anchor for where the data actually sits.
Things to keep in mind
Risks and trade-offs to weigh before adopting Gigasheet.
- The User-Provided Public Data clause in the terms gives Gigasheet a perpetual, commercializable license over any public data you upload
- Stored data can be deleted at any time and at Gigasheet's sole discretion on the free tier and after cancellation or downgrade
- No refunds are granted, even partial, and prices can change on one month's notice
- Sheet Assistant prompts and file metadata leave for OpenAI, which is worth knowing before pasting sensitive column names
- GDPR compliance is admittedly incomplete, data is processed in the United States, and no DPA or subprocessor list is published
- Gigasheet does not verify provider credentials or licenses and does not guarantee the accuracy of source data; displayed rates are not patient quotes
- Mandatory arbitration and a class action waiver apply, under Virginia law
Setup & Integrations
Technical difficulty
Low for normal use. Everything runs in a browser, with no download and no installation. An account is free to create, and Google, Microsoft or GitHub SSO is available. Filtering, grouping, aggregating and pivoting require no query language and no code, and the publisher says analysis can start on day one. Difficulty rises only at the edges: the REST API needs a key and developer skills, with Python examples in the documentation, and any configuration work such as third-party integrations, automations or customizations requires the annual subscription to be paid in full first.
Deployment
Integrations
Behind Gigasheet
Fundraising
Social
Resources
All the official URLs gathered for verification and reference.
Alternatives
Tools that compete with or complement Gigasheet.
Frequently asked questions
What data does Gigasheet analyze?
What is a Smart Rate?
What is a Provider Rate Score?
Is there an API?
Which files can the MRF Viewer open?
Is my data used to train AI models?
Is Gigasheet GDPR compliant?
What security certifications does Gigasheet hold?
Is there a free plan, and where do paid tiers start?
Does Gigasheet replace claims data?
Should you pick Gigasheet?
Gigasheet is a deliberately narrow product. It is no longer the general-purpose big-data spreadsheet its legal pages still describe: what it sells today is US healthcare price transparency, built on public payer and hospital disclosures plus the NPPES registry. Judged on that promise, it delivers two things few rivals manage at once. Scale, with more than 150 billion negotiated rates queryable without any ETL work. And traceability, with every benchmark unrolling down to the published record behind it. The second point matters most, because a rate used in a contract negotiation is only worth the evidence supporting it.
The security foundation is serious for a company this size: SOC 2 Type 2 under continuous third-party audit, NIST 800-171, AWS hosting, AES 256 at rest and TLS in transit, and a stated refusal to train AI models on customer data. Gigasheet is also unusually candid about what public price data cannot tell you. It can be incomplete, outdated or misattributed, it is not a patient quote, and rate scores say nothing about clinical quality.
Two reservations remain. Pricing on the healthcare side is opaque, since everything meaningful goes through a quote request and the self-service grid is not even on the pricing page. And the GDPR position is openly incomplete, written plainly by the publisher itself, with no Article 27 representative, no DPA and no subprocessor list, which will stop some European buyers before the first demo.
For a US provider, payer, self-insured employer or MedTech team that needs defensible rate evidence, Gigasheet is a strong candidate, and the permanent free account lets you judge the engine before spending anything. Outside that scope, it is simply the wrong tool.
- Choosing a selection results in a full page refresh.
- Opens in a new window.