Sematext Cloud
sematext.comSend infrastructure metrics, logs, traces, and synthetic checks to a hosted observability workspace.
Send infrastructure metrics, logs, traces, and synthetic checks to a hosted observability workspace.
Collect and search distributed traces to locate latency and dependency problems across services.
AI-guided cloud-native observability for telemetry, service health, and cost control.
Keep team documents, wiki pages, templates, and approvals on infrastructure you control.
An open-source service-virtualization tool for replacing network dependencies with configurable test doubles.
A project and portfolio management workspace with Gantt plans, tasks, resources, and time capture.
Send time-series metrics to a managed Graphite service with Grafana dashboards and alerting.
AI work management with agents, tasks, docs, and meetings in one workspace
Field service management software for home service contractors
AI chatbot platform that answers customer questions from your own content, live in about 10 minutes.
Collaborative pages and workspaces with components that stay synchronized across Microsoft apps.
Automate repository workflows in a self-hosted Gitea instance.
An AI notebook that checks facts, links related ideas, and helps keep notes current.
Collect team knowledge in searchable notebooks with links, tags, and collaborative editing.
A Markdown notebook that keeps notes in a Git-backed repository and works in the browser or desktop apps.
Turn lease documents into reviewed accounting data and reports
A structured company playbook for documenting processes, policies, and standard procedures.
Local Markdown notebooks with backlinks, search, and optional self-hosted encrypted sync.
Keep a small set of color-coded text notes close at hand across Apple devices.
A company wiki with linked pages, freshness checks, and cited answers from the team’s documentation.
Capture daily notes in local Markdown files and connect ideas with backlinks.
A guided daily planner for timeboxing tasks, reviewing the week, and coordinating connected work.
Fit, evaluate, and reuse Python models for common supervised and unsupervised machine-learning tasks.
Turn instructional recordings and existing materials into reusable technical or training documentation.