Clawbot
DevOpsClawbot improves Tet Threat with identifying stealthy malware and new threats quickly. Secure your data.
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Tick Compare on any two to four cards to put them side by side.
Clawbot improves Tet Threat with identifying stealthy malware and new threats quickly. Secure your data.
Record tests quickly and run them in parallel without a QA team, but requires manual intervention for detailed coverage analysis.
Experiment, train, deploy with one platform. Go from idea to production without replatforming.
Unified access to LLMs via a single API.
Suits regulated enterprises, does not fit small startups.
Great for quick test automation but lacks detailed code maintenance tools.
Build state machines with Stately, but lacks deep code integration.
Build a private website without sharing content.
Limited to AI simulations, not full cloud or data science development.
Rent GPUs for AI and ML at real-time, transparent prices.
Pairs quiz generation and a learning chatbot with a built-in bug-reporting sidebar.
Suits industrial AI, does not excel at consumer use.
AI-generated questions, but with limited results analysis.
Puts a sidebar of R&D tools, GPT-4 and Midjourney access into one internal browser panel.
Answers plain-language questions about building codes, trained specifically for structural engineering.
Adds one-click buttons that post pipeline-trigger comments on GitHub pull requests.
NopeCHA for Chrome solves all CAPTCHA types.
Improves Tet by identifying poor data usage.
Two-factor auth, quick login.
Langtail is essential for managing unpredictable AI outputs.
Automates code reviews with AI, saving time and improving quality.
Translates natural language to Linux commands.
Turns a GitLab issue title into a branch name, using your own OpenAI key.
Join us to help ensure AI wins for democracy. Challenges we face are redesigning compute infrastructure and deploying gigawatts of solar.
Online assessment and proctoring solutions.
DuoSoft offers custom software, AI integration, and digital transformation projects tailored for organizations but may not handle simpler web development tasks.
Best for secure on-premises AI deployment, not cloud-based solutions.
Unified platform for app and AI testing.
41 vetted SaaS boilerplates
Achieve near zero false positives with over 99% defect detection accuracy, deploy in just a few days.
Too rigid for manual workflows.
Enables AI and autonomy in various industries.
All Quiet streamlines on-call management and incident response for engineering teams.
No-code editor for complex trading algorithms.
Provides ticket suggestions for MSPs.
A token-powered marketplace connecting AI developers with GPU compute, backed by its own data centre.
Manage AI prompts with version control and testing.
Non-technical team members should use PromptPoint, not software engineers.
Specialized language models for real-world business decisions. All data stays in Europe.
Free to self-host, but lacks hosted option.
Centralize all your AI agents in one channel, but it lacks complex integrations.
Runs AI workloads locally but lacks built-in Kubernetes management.
Generates test ideas from a webpage's elements, then turns them into ready-to-run automation scripts.
Tacnique streamlines your hiring with virtual interviews and expert recruitment.
Supertest rapidly collects actionable insights, but it requires a panel of participants rather than allowing you to use your own.
Monitor uptime, performance, and incidents.
Antibot solution, prevents automated attacks.
Deploy AI models at sub-second cold starts, run them on any GPU. Perfect for rapid inference and training.
Three worth starting with
Terms to know
DevOps tools cover the work between writing code and keeping it running: deploying, monitoring, managing containers and cloud workloads. Listings here include K8sStudio for Kubernetes and Autobot AI for workflow automation, alongside some general browser utilities. Look at which part of the pipeline a tool touches and whether it needs write access to production systems.
They can explain cluster state, suggest commands and draft configuration, which helps with debugging. Letting an AI apply changes directly to production is a bigger step. Most teams keep a human approval step and review generated manifests before they run.
Common uses are writing and explaining pipeline files, reading logs, summarising incidents and drafting runbooks. The tools save time on repetitive text and configuration, but they do not know your environment, so every suggested command still needs checking.
DevOps is about delivering and operating software reliably. Network security focuses on protecting systems from attack, and API development on building the interfaces between services. The three overlap in practice, especially around secrets and access control.