
You know the pain. 8,000+ formulas in your Excel budget, any one of which could break. Department heads emailing versions back and forth. Mystery errors appearing right before board meetings. Weekends lost hunting for that one number that doesn't add up.
We built Budgyt because we lived that nightmare as CFOs ourselves.
It's a true database that works like Excel, so your team doesn't need training. But formulas never break. Every number traces back to source with one click. Import your chart of accounts and actuals directly from your accounting system. Click any variance to drill down to vendor-level detail instantly. Run rolling reforecasts every month without rebuilding everything from scratch.
We connected it via API so you're up and running in hours, not spending months on implementation consulting.
Built for multi-department organizations where budgeting needs to be collaborative, but the finance team needs to stay in control. No more emailing spreadsheets around. No more "did I break something?" panic. Just budgeting that actually works.
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Pipefy is a low-code Business Orchestration and Automation Technologies (BOAT) platform designed to act as a modern middleware layer for the enterprise stack.
Rather than replacing existing Systems of Record (SORs) like SAP, Oracle, or Salesforce, Pipefy wraps them in an agile orchestration layer. This architecture allows technical teams to modernize legacy operations and extend the life of core systems without the risks associated with "rip and replace" projects. Pipefy provides the infrastructure to sanitize data inputs, manage complex business logic, and orchestrate API calls between fragmented endpoints.
Technical & Architectural Highlights:
• Adaptive Governance Framework: Pipefy solves the "Shadow IT" problem by establishing IT-sanctioned "Safe Zones." Business users can build workflows within these guardrails, while IT retains control over critical data, integrations, and permissions via a centralized console.
• Agentic AI Engine (BYOLLM): The platform features a governable AI Agent Studio. Unlike "black box" solutions, Pipefy supports a Bring Your Own LLM approach, allowing enterprises to integrate preferred models (Azure OpenAI, AWS Bedrock) securely to automate document analysis (OCR) and decision-making.
• Robust Connectivity: Built with an API-first philosophy, Pipefy offers a GraphQL API, Webhooks, and enterprise-grade iPaaS capabilities to ensure seamless data interoperability across the stack.
• Security & Compliance: Engineered for regulated industries, the platform is ISO 27001, ISO 27701, and SOC2 Type II certified, supporting compliance with GDPR and SOX standards.
Pipefy empowers IT leaders to eliminate technical debt and clear development backlogs by safely delegating low-complexity builds to business units.
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SPC for Excel
SPC for Excel, a simple but powerful package, to handle all your SPC and statistical analysis needs. SPC for Excel software allows you to identify problem areas, gain insight into your data, spot trends and solve problems. All this in Excel. From the novice to the black belt, SPC for Excel will facilitate your process improvement efforts – in any industry – profit or non-profit.
Get all the techniques you need for your charting and analysis – including Pareto diagrams, Histogram, Control Charts, Gage R&R, Process Capability, Distribution Fitting, Data Transformation, Regression, DOE, Hypothesis Testing, and more! One time payment – yours forever. Two downloads per user and free Technical support. Try out our Demo – see how easy it is!
Process Capability analysis - to meet customer needs
Control charts and histograms - to manage processes
Gage R&R Studies – To validate your measurement system
Problem Solving Tools (Pareto and histogram, scatter, etc.) - to help your group solve problems
Advanced Data Analysis Tools (DOE and ANOVA, distribution fittings, regression, hypotheses testing and more) are available to meet your advanced requirements.
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QMSys GUM
The QMSys GUM Software is designed for assessing the uncertainty inherent in physical measurements, chemical analyses, and calibration processes. It employs three distinct methodologies to compute measurement uncertainty. The first, GUF Method for linear models, targets linear and quasi-linear models, aligning with the GUM Uncertainty Framework. This approach calculates partial derivatives, representing the initial terms of a Taylor series, to ascertain sensitivity coefficients for the equivalent linear model, followed by the determination of combined standard uncertainty using the Gaussian error propagation law. The second, GUF Method for nonlinear models, caters to nonlinear models where results exhibit symmetric distribution. This method incorporates various numerical techniques, including nonlinear sensitivity analysis and higher-order sensitivity indices, as well as quasi-Monte Carlo simulations utilizing Sobol sequences. With its multifaceted approach, the software provides comprehensive tools for uncertainty analysis across different measurement contexts.
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