The Diabetes Risk Assessment API leverages advanced AI and machine learning algorithms to evaluate individual health metrics and deliver a classification of diabetes risk as either 'Positive' or 'Negative'.

Screen cancer risk from routine CBC blood tests in <50ms. Returns risk tiers for prostate, breast, lung, colorectal cancer & multi-cancer alert. No PII required.

The Joyful Insights Forecasting (AI) API delivers emotional classification results, categorizing input data as either 'Happy' or 'Unhappy'. Utilizing advanced machine learning techniques, this API specializes in sentiment analysis to provide accurate predictions. For further details about the underlying model and its capabilities, please reach out to us.

Accepts a structured description of a working relationship and returns a jurisdiction-specific misclassification risk score (0-100), risk level, factor-by-factor analysis, and plain-English reasoning across 20 jurisdictions. Also includes remediation guidance, safe-harbor checklists, financial exposure estimation, cross-jurisdiction comparison, and portfolio-level bulk scoring. No database, no runtime scraping — fast and deterministic responses.

Detect machine-generated text using statistical heuristics.

Classify content into IAB categories using tiered and unified prediction endpoints.

The Multilingual Detector API is a tool that allows users to determine the language of a given piece of text with a confidence score.

Descriptive statistics, normality, correlation, and process capability (Cp/Cpk/Pp/Ppk) as a JSON API. Send a data table and a config, get clean result tables back.

Advanced multimodal AI API that analyzes images, audio, and video — extracting text, scene descriptions, and visual/audio context in one unified request.

Edge case test data for QA and fuzz testing: Unicode, injection probes, boundary dates, float precision. 16 types, reproducible seeds, and every value explains what it breaks.

The BigFive Sentiment Analysis API uses advanced machine learning algorithms to analyze text and determine the emotions and personality traits expressed within it. It can classify text into five main categories: Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism, and provide the results in a structured format.

Stay ahead in patient care with the Innovative Innovative AI Cancer Risk API, integrating cutting-edge technology for cancer risk analysis.

Unicode test data for internationalization testing: combining marks, bidi overrides, ZWJ emoji, homoglyphs. Deterministic seeds, and every value explains what it breaks.

Boundary value test data for off-by-one bugs: int32 and int64 limits, max-length strings, empty values. Deterministic seeds, and every value explains what it breaks.

Canonical injection test strings for checking your own escaping: SQL tautology, XSS, path traversal, template injection. Harmless probes, not working exploits. Reproducible seeds.

Integer and floating-point edge cases: int32/int64 limits, NaN, infinity, denormals, and IEEE 754 rounding. Deterministic seeds, and every value explains what it breaks.

Fuzz testing input data for validation layers: malformed strings, boundary values, control characters. 16 field types, reproducible seeds; each value explains what it breaks.

QA test fixtures and CI seed data with reproducible seeds, so pinned test runs return identical rows every time. 16 field types, each value explaining what it breaks.

Malformed and hostile string test data for input handling: control characters, null bytes, encoding edge cases. Reproducible seeds, and every value explains what it breaks.

Date and time edge cases: Feb 29, DST gaps, year 2038, leap seconds, and quarter-hour UTC offsets. Reproducible seeds, and every value explains what it breaks.

Score one working relationship across up to 5 jurisdictions at once, or compare jurisdictions' legal tests and penalty exposure side by side, to find the safest place to engage a role.

Score IR35 and off-payroll working risk for UK engagements, alongside 19 other jurisdictions' classification tests, with factor-by-factor reasoning.

Score misclassification risk (0–100) across 20 jurisdictions from a structured description of a working relationship, with the legal test applied and factor-by-factor reasoning.

Bulk-score up to 100 existing contractor relationships in one call, with per-worker risk levels and aggregate statistics to flag your highest-risk workers first.

Score misclassification risk before placing a worker in any of 20 jurisdictions, with financial exposure estimates and remediation guidance for EOR and payroll teams.