# Preteckt

**Canonical:** https://apis.io/providers/preteckt/  
**Website:** https://preteckt.com  
**APIs profiled:** 0

Preteckt provides AI-powered predictive maintenance for transit buses, coach buses, and trucking fleets. Its platform ingests vehicle sensor telemetry and applies machine-learning algorithms to detect maintenance issues before they cause breakdowns, reducing diagnostic time by nearly 50 percent and preventing roughly 20 percent of failures. Preteckt processes more than one million sensor data points per day per vehicle across 20+ maintenance-focused algorithms. The company is part of Diesel Laptops. It was surfaced as a portfolio company of 500 Global and added to the API Evangelist network. As of this enrichment pass Preteckt publishes no public developer, API, documentation, or sign-up surface.

## Kin Score — 10.6 / 100 (minimal)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 10.6).

| Facet | Score |
|---|---|
| Discoverability | 50.0 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 7.1 |
| Commercial Clarity | 21.1 |
| Access Clarity | 21.1 |

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |

## Access

Unknown — onboarding: unknown, pricing: unknown, trial: no (confidence: low).

## Security (1)

- **Preteckt Domain Security** — TLSv1.3 · DNSSEC · DMARC

## Tags

Company, Predictive Maintenance, Fleet Management, Transportation, Automotive, Machine-Learning, Telematics, IoT

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Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/preteckt/). Scores are computed from the provider's own public artifacts under a published rubric.