619 Integrations with TypeScript
View a list of TypeScript integrations and software that integrates with TypeScript below. Compare the best TypeScript integrations as well as features, ratings, user reviews, and pricing of software that integrates with TypeScript. Here are the current TypeScript integrations in 2026:
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Solid
Solid
Solid is an AI-powered full-stack app builder that enables both technical and non-technical users to create, customize, and launch production-ready web applications, just as easily as making a TikTok. Unlike lightweight tools like Lovable or Base44 that generate superficial front-end facades, Solid delivers a complete, extendable codebase: a Node.js backend with Prisma ORM, a React + TypeScript frontend, and a seamlessly connected database, just like what professional developers use. You can import toy projects built with Lovable/Base44 and instantly transform them into robust, real apps that are scalable, transparent, and transferable. Solid supports deep customization; you own every layer (frontend, backend, data), allowing you to add complex business logic, REST or GraphQL APIs, and integrations effortlessly. It generates high-quality, inspectable code you can deploy anywhere, from Solid’s platform to your cloud, without vendor lock-in. -
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Sudo
Sudo
Sudo offers “one API for all models”, a unified interface so developers can integrate multiple large language models and generative AI tools (for text, image, audio) through a single endpoint. It handles routing between different models to optimize for things like latency, throughput, cost, or whatever criteria you choose. The platform supports flexible billing and monetization options; subscription tiers, usage-based metered billing, or hybrids. It also supports in-context AI-native ads (you can insert context-aware ads into AI outputs, controlling relevance and frequency). Onboarding is quick: you create an API key, install their SDK (Python or TypeScript), and start making calls to the AI endpoints. They emphasize low latency (“optimized for real-time AI”), better throughput compared with some alternatives, and avoiding vendor lock-in. -
3
Claude Sonnet 4.5
Anthropic
Claude Sonnet 4.5 is Anthropic’s latest frontier model, designed to excel in long-horizon coding, agentic workflows, and intensive computer use while maintaining safety and alignment. It achieves state-of-the-art performance on the SWE-bench Verified benchmark (for software engineering) and leads on OSWorld (a computer use benchmark), with the ability to sustain focus over 30 hours on complex, multi-step tasks. The model introduces improvements in tool handling, memory management, and context processing, enabling more sophisticated reasoning, better domain understanding (from finance and law to STEM), and deeper code comprehension. It supports context editing and memory tools to sustain long conversations or multi-agent tasks, and allows code execution and file creation within Claude apps. Sonnet 4.5 is deployed at AI Safety Level 3 (ASL-3), with classifiers protecting against inputs or outputs tied to risky domains, and includes mitigations against prompt injection. -
4
Agent Builder
OpenAI
Agent Builder is part of OpenAI’s tooling for constructing agentic applications, systems that use large language models to perform multi-step tasks autonomously, with governance, tool integration, memory, orchestration, and observability baked in. The platform offers a composable set of primitives—models, tools, memory/state, guardrails, and workflow orchestration- that developers assemble into agents capable of deciding when to call a tool, when to act, and when to halt and hand off control. OpenAI provides a new Responses API that combines chat capabilities with built-in tool use, along with an Agents SDK (Python, JS/TS) that abstracts the control loop, supports guardrail enforcement (validations on inputs/outputs), handoffs between agents, session management, and tracing of agent executions. Agents can be augmented with built-in tools like web search, file search, or computer use, or custom function-calling tools. -
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PromptCompose
PromptCompose
PromptCompose is a prompt infrastructure platform designed to bring software engineering rigor to prompt workflows. It offers version control for prompts, automatically tracking every change with deployment logs, side-by-side comparisons, and rollback capability, and integrates AB testing so multiple prompt variants can run concurrently, traffic can be split, performance tracked, and winners deployed confidently. Developers can integrate seamlessly via SDKs (JavaScript/TypeScript) or REST APIs so prompts and experiments can be part of production systems. Projects are organized in a hub structure so teams can manage resources (prompts, templates, variable groups, tests) per project, with proper isolation and collaboration. PromptCompose supports prompt blueprints (templates) and variable groups so prompts can be parameterized with dynamic inputs in a consistent, reusable way. The editor includes features like syntax highlighting, autocomplete for variables, and error detection. -
6
RKTracer
RKVALIDATE
RKTracer is a code-coverage and test-analysis tool that enables teams to assess the quality and completeness of their testing across unit, integration, functional, and system-level testing, without altering a single line of application code or build workflow. It supports instrumentation across host machines, simulators, emulators, embedded devices, and servers, and covers a broad array of programming languages, including C, C++, CUDA, C#, Java, Kotlin, JavaScript/TypeScript, Golang, Python, and Swift. It provides detailed coverage metrics such as function, statement, branch/decision, condition, MC/DC, and multi-condition coverage, and even supports delta-coverage reports to show which newly added or modified portions of code are already covered. Integration is seamless; simply prefix your build or test command with “rktracer”, run your tests, then generate HTML or XML reports (for CI/CD systems or dashboards like SonarQube). -
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Tailark Pro
Tailark Pro
Tailark Pro is a premium marketing UI kit made to help teams ship beautiful websites fast. Instead of spending days designing layouts, you get a large collection of polished, conversion-ready blocks : hero sections, feature highlights, pricing tables, testimonials, CTAs, and more, plus complete, ready-to-use pages like landing pages, product pages, solution pages, and blogs. Everything is built with shadcn/ui, Tailwind CSS, Next.js, and TypeScript, so the components feel natural in modern React projects. No learning curve, no lock-in, and no complicated setup. Just clean, editable code you can plug into your existing project. Tailark Pro is perfect for startups, agencies, and product teams who want to move faster, keep quality high, and stay consistent across all marketing pages. You get a professional design foundation that’s easy to customize to your brand — so you can focus on your product, not rebuilding the same sections over and over.Starting Price: $249 -
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GPT-5.1 Instant
OpenAI
GPT-5.1 Instant is a high-performance AI model designed for everyday users that combines speed, responsiveness, and improved conversational warmth. The model uses adaptive reasoning to instantly select how much computation is required for a task, allowing it to deliver fast answers without sacrificing understanding. It emphasizes stronger instruction-following, enabling users to give precise directions and expect consistent compliance. The model also introduces richer personality controls so chat tone can be set to Default, Friendly, Professional, Candid, Quirky, or Efficient, with experiments in deeper voice modulation. Its core value is to make interactions feel more natural and less robotic while preserving high intelligence across writing, coding, analysis, and reasoning. GPT-5.1 Instant routes user requests automatically from the base interface, with the system choosing whether this variant or the deeper “Thinking” model is applied. -
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GPT-5.1 Thinking
OpenAI
GPT-5.1 Thinking is the advanced reasoning model variant in the GPT-5.1 series, designed to more precisely allocate “thinking time” based on prompt complexity, responding faster to simpler requests and spending more effort on difficult problems. On a representative task distribution, it is roughly twice as fast on the fastest tasks and twice as slow on the slowest compared with its predecessor. Its responses are crafted to be clearer, with less jargon and fewer undefined terms, making deep analytical work more accessible and understandable. The model dynamically adjusts its reasoning depth, achieving a better balance between speed and thoroughness, particularly when dealing with technical concepts or multi-step questions. By combining high reasoning capacity with improved clarity, GPT-5.1 Thinking offers a powerful tool for tackling complex tasks, such as detailed analysis, coding, research, or technical explanations, while reducing unnecessary latency for routine queries. -
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Gemini 3 Deep Think
Google
The most advanced model from Google DeepMind, Gemini 3, sets a new bar for model intelligence by delivering state-of-the-art reasoning and multimodal understanding across text, image, and video. It surpasses its predecessor on key AI benchmarks and excels at deeper problems such as scientific reasoning, complex coding, spatial logic, and visual-/video-based understanding. The new “Deep Think” mode pushes the boundaries even further, offering enhanced reasoning for very challenging tasks, outperforming Gemini 3 Pro on benchmarks like Humanity’s Last Exam and ARC-AGI. Gemini 3 is now available across Google’s ecosystem, enabling users to learn, build, and plan at new levels of sophistication. With context windows up to one million tokens, more granular media-processing options, and specialized configurations for tool use, the model brings better precision, depth, and flexibility for real-world workflows. -
11
Bask
Bask
Bask is a fully-featured, HIPAA-compliant telehealth and ecommerce solution designed to support entrepreneurs, doctors, and developers in launching and scaling direct-to-consumer digital health services. It includes a drag-and-drop questionnaire and patient-portal builder, brandable no-code launch tools, payment-processing capabilities, telehealth video visits, built-in e-prescribing, and pharmacy-fulfillment integration across all 50 states, all housed under a single unified platform. With security features such as strong encryption, multi-factor authentication, and audit logging, it builds on enterprise-grade architecture while remaining accessible to non-technical users. Analytics dashboards offer real-time insights into patient flows, order status, cohort behavior, and key performance indicators. It supports multiple business models, from subscription-based care to on-demand consults, and integrates with APIs and external systems. -
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Claude Opus 4.5
Anthropic
Claude Opus 4.5 is Anthropic’s newest flagship model, delivering major improvements in reasoning, coding, agentic workflows, and real-world problem solving. It outperforms previous models and leading competitors on benchmarks such as SWE-bench, multilingual coding tests, and advanced agent evaluations. Opus 4.5 also introduces stronger safety features, including significantly higher resistance to prompt injection and improved alignment across sensitive tasks. Developers gain new controls through the Claude API—like effort parameters, context compaction, and advanced tool use—allowing for more efficient, longer-running agentic workflows. Product updates across Claude, Claude Code, the Chrome extension, and Excel integrations expand how users interact with the model for software engineering, research, and everyday productivity. Overall, Claude Opus 4.5 marks a substantial step forward in capability, reliability, and usability for developers, enterprises, and end users. -
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GPT-5.2
OpenAI
GPT-5.2 is the newest evolution in the GPT-5 series, engineered to deliver even greater intelligence, adaptability, and conversational depth. This release introduces enhanced model variants that refine how ChatGPT reasons, communicates, and responds to complex user intent. GPT-5.2 Instant remains the primary, high-usage model—now faster, more context-aware, and more precise in following instructions. GPT-5.2 Thinking takes advanced reasoning further, offering clearer step-by-step logic, improved consistency on multi-stage problems, and more efficient handling of long or intricate tasks. The system automatically routes each query to the most suitable variant, ensuring optimal performance without requiring user selection. Beyond raw intelligence gains, GPT-5.2 emphasizes more natural dialogue flow, stronger intent alignment, and a smoother, more humanlike communication style. -
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Grok 4.1 Thinking
SpaceXSI
Grok 4.1 Thinking is xAI’s advanced reasoning-focused AI model designed for deeper analysis, reflection, and structured problem-solving. It uses explicit thinking tokens to reason through complex prompts before delivering a response, resulting in more accurate and context-aware outputs. The model excels in tasks that require multi-step logic, nuanced understanding, and thoughtful explanations. Grok 4.1 Thinking demonstrates a strong, coherent personality while maintaining analytical rigor and reliability. It has achieved the top overall ranking on the LMArena Text Leaderboard, reflecting strong human preference in blind evaluations. The model also shows leading performance in emotional intelligence and creative reasoning benchmarks. Grok 4.1 Thinking is built for users who value clarity, depth, and defensible reasoning in AI interactions. -
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GPT-5.2-Codex
OpenAI
GPT-5.2-Codex is OpenAI’s most advanced agentic coding model, built for complex, real-world software engineering and defensive cybersecurity work. It is a specialized version of GPT-5.2 optimized for long-horizon coding tasks such as large refactors, migrations, and feature development. The model maintains full context over extended sessions through native context compaction. GPT-5.2-Codex delivers state-of-the-art performance on benchmarks like SWE-Bench Pro and Terminal-Bench 2.0. It operates reliably across large repositories and native Windows environments. Stronger vision capabilities allow it to interpret screenshots, diagrams, and UI designs during development. GPT-5.2-Codex is designed to be a dependable partner for professional engineering workflows. -
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Bun
Bun
Bun is a fast, all-in-one JavaScript, TypeScript, and JSX toolkit that ships as a single executable and combines a high-performance runtime, package manager, test runner, and bundler designed as a drop-in replacement for Node.js with broad compatibility and dramatically reduced startup times and memory usage. Written in Zig and powered by Apple’s JavaScriptCore, Bun can execute JavaScript/TypeScript files, scripts, and packages with significantly faster performance than traditional tooling while supporting zero-config TypeScript, JSX, and React out of the box. Its built-in package manager installs dependencies up to 30x faster than npm with workspaces, global caching, migration support, and dependency auditing. Bun’s test runner is Jest-compatible with built-in coverage and concurrent execution, and the bundler processes TypeScript, JSX, CSS, and more without configuration, including support for single-file executables.xx -
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LemonadeJS
Jspreadsheet
Agnostic Micro Reactive JavaScript Library. LemonadeJS is a dependency-free lightweight library featuring an abstract reactive layer and two-way data binding. It enables the creation of modern platform-agnostic components using pure JavaScript, JSX, or TypeScript. -
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GPT-5.3-Codex
OpenAI
GPT-5.3-Codex is OpenAI’s most advanced agentic coding model, designed to handle complex professional work on a computer. It combines frontier-level coding performance with advanced reasoning and real-world task execution. The model is faster than previous Codex versions and can manage long-running tasks involving research, tools, and deployment. GPT-5.3-Codex supports real-time interaction, allowing users to steer progress without losing context. It excels at software engineering, web development, and terminal-based workflows. Beyond code generation, it assists with debugging, documentation, testing, and analysis. GPT-5.3-Codex acts as an interactive collaborator rather than a single-turn coding tool. -
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Gemini 3.1 Pro
Google
Gemini 3.1 Pro is Google’s upgraded core intelligence model designed for complex tasks that require advanced reasoning. Building on the Gemini 3 series, it delivers significant improvements in problem-solving performance and logical pattern recognition. On the ARC-AGI-2 benchmark, Gemini 3.1 Pro achieved a verified score of 77.1%, more than doubling the reasoning performance of Gemini 3 Pro. The model is engineered for challenges where simple answers are insufficient, enabling deeper analysis, synthesis, and creative output. It can generate practical outputs such as animated, website-ready SVGs directly from text prompts, combining intelligence with real-world usability. Gemini 3.1 Pro is rolling out in preview across consumer, developer, and enterprise platforms including the Gemini app, NotebookLM, Gemini API, Gemini Enterprise Agent Platform, and Android Studio. With expanded access for Google AI Pro and Ultra users, 3.1 Pro sets a stronger baseline for agentic workflows. -
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Gemini 3.1 Flash-Lite
Google
Gemini 3.1 Flash-Lite is Google’s fastest and most cost-efficient model in the Gemini 3 series, designed for high-volume developer workloads. It delivers strong performance at scale while maintaining affordability, with pricing set at $0.25 per million input tokens and $1.50 per million output tokens. The model significantly improves speed, offering a 2.5x faster time to first answer token and a 45% increase in output speed compared to Gemini 2.5 Flash. Despite its lower cost tier, it achieves high benchmark results, including an Elo score of 1432 and strong performance across reasoning and multimodal evaluations. Gemini 3.1 Flash-Lite supports adaptive “thinking levels,” allowing developers to control how much reasoning power is used for different tasks. It is suitable for large-scale applications such as translation, content moderation, user interface generation, and simulation building. -
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GPT-5.3 Instant
OpenAI
GPT-5.3 Instant is an updated version of ChatGPT’s most-used model, designed to make everyday conversations more fluid, helpful, and accurate. The release focuses on improving tone, relevance, and conversational flow based directly on user feedback. It reduces unnecessary refusals and cuts back on overly cautious disclaimers, delivering clearer and more direct answers when appropriate. The model also improves how it integrates web results, providing better-contextualized information rather than long lists of loosely connected links. Accuracy has been strengthened, with measurable reductions in hallucinations across both high-stakes domains and everyday queries. GPT-5.3 Instant enhances creative writing capabilities, producing more textured, emotionally resonant prose. It is available to all ChatGPT users and developers via the API under ‘gpt-5.3-chat-latest,’ with legacy versions scheduled for retirement. -
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GPT-5.4 Pro
OpenAI
GPT-5.4 Pro is an advanced AI model developed by OpenAI to deliver high-performance capabilities for professional and complex tasks. It combines improvements in reasoning, coding, and agent-based workflows into a single unified system. The model is designed to work efficiently across professional tools such as spreadsheets, presentations, documents, and development environments. GPT-5.4 Pro also includes native computer-use capabilities, enabling AI agents to interact with software, websites, and operating systems to complete tasks. With support for up to one million tokens of context, it can manage long workflows and large datasets more effectively than previous models. The model also improves tool usage, allowing it to search for and select the right tools during multi-step processes. By delivering more accurate outputs with fewer tokens, GPT-5.4 Pro helps professionals complete complex work faster and more efficiently. -
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GPT‑5.4 Thinking
OpenAI
GPT-5.4 Thinking is an advanced reasoning-focused AI model available within ChatGPT, designed to help users complete complex professional tasks more effectively. It combines improvements in reasoning, coding, and agent-based workflows to provide more accurate and reliable outputs. The model can present an upfront outline of its reasoning process, allowing users to adjust instructions while it is generating a response. This capability helps produce results that better align with user goals without requiring multiple follow-up prompts. GPT-5.4 Thinking also improves deep web research, enabling it to locate and synthesize information from multiple sources more efficiently. With stronger context management, it can handle longer conversations and complex problem-solving tasks with greater coherence. These capabilities make GPT-5.4 Thinking well suited for professional knowledge work and advanced analytical tasks. -
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GPT-5.4 mini
OpenAI
GPT-5.4 mini is a fast and efficient AI model designed for high-performance tasks such as coding, reasoning, and multimodal understanding. It delivers strong capabilities similar to larger models while maintaining lower latency and cost. The model is optimized for responsive applications where speed is critical, including coding assistants and real-time workflows. GPT-5.4 mini supports advanced features such as tool use, function calling, and image interpretation. It performs well on complex tasks while running significantly faster than previous mini models. The model is also suitable for subagent systems, where it handles smaller tasks within larger AI workflows. By combining speed, efficiency, and strong performance, GPT-5.4 mini enables scalable AI applications across various use cases. -
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GPT-5.4 nano
OpenAI
GPT-5.4 nano is a lightweight and highly efficient AI model designed for fast, cost-effective task execution. It is optimized for simple and high-volume tasks such as classification, data extraction, and basic coding support. The model delivers quick responses with minimal latency, making it ideal for real-time and large-scale applications. GPT-5.4 nano improves significantly over previous nano models in both performance and efficiency. It supports essential capabilities like tool use and structured data processing. The model is commonly used as a supporting component within larger AI systems. By focusing on speed and affordability, GPT-5.4 nano enables scalable automation across various workflows. -
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Simaril
Simaril
Silmaril is a self-healing prompt injection defense designed to protect AI systems from increasingly complex, multi-step attacks that traditional guardrails fail to stop. It operates by wrapping inference calls and evaluating whether an execution sequence is leading toward a harmful outcome, rather than simply filtering inputs. It uses a multihead classifier that analyzes user intent, application context, and execution states together, enabling it to detect indirect injection, multi-turn attack chains, context poisoning, and tool abuse before damage occurs. Silmaril continuously strengthens its defenses through autonomous threat hunting agents that probe systems, discover vulnerabilities, and generate synthetic training data from real attack scenarios. These insights are used to retrain the model automatically, deploying updated protections in under an hour and propagating anonymized defenses across all deployments. -
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ERNIE 5.1
Baidu
ERNIE 5.1 is Baidu’s latest large language model designed to deliver advanced reasoning, agentic AI capabilities, creative writing, and world knowledge performance while operating with significantly improved efficiency. The model builds on the foundation of ERNIE 5.0 while reducing total parameters and training costs, allowing it to achieve flagship-level intelligence at a fraction of the computational expense of comparable models. ERNIE 5.1 performs strongly across international benchmarks for reasoning, search, knowledge, and agentic tasks, ranking among the top global AI models and leading among Chinese-developed models on multiple leaderboards. The platform introduces a new fully asynchronous reinforcement learning infrastructure that improves training efficiency, scalability, and stability for complex long-horizon AI tasks. ERNIE 5.1 also features advanced creative writing capabilities. -
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GraphBit
GraphBit
GraphBit is an enterprise-grade agentic AI framework built to run critical AI systems with security, governance, and predictable production performance. It combines a Rust execution core with a Python wrapper to give developers high-performance orchestration with the accessibility of Python, helping teams build reliable multi-agent workflows with minimal CPU and memory usage. GraphBit is designed around the layers that reduce risk, including interfaces, configuration, models, tools, actions, memory, orchestration, and observability. It integrates into existing apps, powers custom AI interfaces, and lets users interact through familiar workflows with controlled actions. Teams can define policies, rules, and guardrails centrally, while GraphBit enforces behavior without changing application code. It supports LLMs and multimodal models from multiple providers, allowing teams to swap models freely without breaking workflows or governance. -
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Kelviq
Kelviq
Kelviq is the home of global software monetization, bringing payments, usage billing, tax, and Merchant of Record into one system built for SaaS and AI companies. It gives teams one platform for payments, tax, pricing, and feature access, so they can sell globally without stitching together billing infrastructure. Kelviq supports flexible pricing models, including flat fee, per seat, usage, volume, credits, one-time payments, overages, and hybrid pricing. It also unifies checkout, real-time usage metering, entitlements, tax compliance, and global payments, allowing teams to run subscriptions, usage, and one-time payments side by side while keeping invoices synced to real usage. Businesses can meter API calls, tokens, AI agents, storage, compute units, active users, or custom units in real time, with invoice line items linked back to raw event logs. -
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Google GenAI SDK
Google
The Gemini API libraries provide official, production-ready Google GenAI SDKs for building with the Gemini API in popular programming languages. Google recommends using the Google GenAI SDK when building with Gemini, since these libraries are developed and maintained by Google, used across official documentation and examples, and are generally available for production use. The SDKs are available for Python, JavaScript/TypeScript, Go, Java, and C#, with installation through standard package managers such as pip install google-genai, npm install google/genai, Maven dependencies for google genai, and dotnet add package Google GenAI. They provide access to the latest Gemini API features and are designed to offer the best performance when working with Gemini models. Google strongly recommends migrating from legacy libraries to the new Google GenAI SDK because the legacy libraries are not actively maintained. -
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Diom
Svix
Diom is a backend components platform for building robust services, offering a set of well-integrated infrastructure primitives for backend and data engineers, including caching, key-value storage, rate-limiting, idempotency, queues, and streams. It is designed so engineers no longer need to build fragile, slow, and hard-to-maintain solutions on top of Redis, Postgres, or other data stores, and can instead rely on powerful, performant, well-tested components built for common backend patterns. Diom can replace multiple services such as Redis, RabbitMQ, and Kafka for many use cases, reducing service dependencies, operational complexity, monitoring overhead, backups, configuration work, and deployment costs. Its components support low-latency operations, minimal round-trip, HTTP-based APIs, SDKs for popular languages, and deployment in common backend environments. -
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TypeGPU
Software Mansion
TypeGPU is a TypeScript library that enhances the WebGPU API, allowing resource management in a type-safe, declarative way. It is designed to change the way developers work with GPU rendering and computing by bringing stronger structure, validation, and developer experience to WebGPU workflows. TypeGPU helps developers easily encode and decode GPU data, using typed binary so they do not have to think about raw bytes when writing GPU programs. Complex data types such as structs and arrays can be described directly, while TypeScript automatically validates outgoing and incoming data. It works on React Native through react-native-wgpu, expanding WebGPU development beyond the browser. TypeGPU’s roadmap is focused on end-to-end type safety on the GPU through interoperating primitives such as data structures, buffers, bind groups, a linker, functions, pipelines, and imperative code. -
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eve
Vercel
Eve is the framework for building agents, like Next.js for web apps, but for agents. It uses Markdown for instructions and skills, TypeScript for tools, and durable execution by default. An agent is a directory that defines instructions and skills in Markdown, tools in TypeScript, and then deploys. Eve compiles the directory, wires up durable workflows, and connects channels, giving developers a structured way to build production agents without gluing together point solutions. An instructions.md file can be a complete agent, while agent.ts lets teams choose a model or configure the runtime. Reusable skills are Markdown playbooks loaded when relevant, so the agent gets focused guidance without carrying everything in every prompt. Tools are added as TypeScript files, with the filename becoming the tool name, and no registration is required. Every agent includes an isolated sandbox and file tools, with support for custom sandbox setup. -
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GPT-5.6 Sol Ultrafast
OpenAI
GPT-5.6 Sol Ultrafast is a new OpenAI API service tier that runs GPT-5.6 Sol up to 14× faster than Standard processing, bringing frontier intelligence to products and workflows where every second matters. Powered by Cerebras, it can generate up to 750 output tokens per second, allowing advanced reasoning to operate at real-time speeds without requiring a smaller or more specialized model. It is designed for time-sensitive business workflows where faster responses can change what AI can realistically do. Applications include incident response, where models can analyze logs, code changes, traces, and engineer reports while an outage is unfolding; financial research and security, where changing market signals and suspicious transactions can be assessed quickly; and customer support and voice, where complex issues can be resolved without interrupting a live conversation. In commerce, it can answer product questions, check inventory, and personalize recommendations. -
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Gemini 3.8 Flash Cyber
Google
Gemini 3.8 Flash Cyber is Google’s most capable cybersecurity model, providing frontier-level performance in vulnerability detection and automated patching with the speed needed for quick iteration. It is designed specifically for trusted defenders and is available through the Fairwind Program. On CyberGym, a standard industry benchmark for finding vulnerabilities, the model demonstrates frontier-level autonomous vulnerability discovery and surpasses both Gemini 3.5 Flash Cyber and significantly larger frontier models. Google also evaluated it on an internal benchmark covering complex codebases across 20 programming languages, where it achieved a success rate exceeding 70% in discovering a wide range of vulnerabilities. Gemini 3.8 Flash Cyber prioritizes vulnerability fixing over offensive capabilities such as exploitation, equipping defenders with expert capabilities that can help them maintain an advantage over attackers. -
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Grok 4.8
SpaceXSI
Grok 4.8 is an upcoming AI model from xAI expected to advance the Grok family in reasoning, coding, agentic workflows, and professional knowledge work. Elon Musk has described the model as having approximately 2.5 trillion parameters and being trained using a new C++ software stack. The model is expected to complete its initial training before entering reinforcement learning, with final capabilities and performance still subject to change. Grok 4.8 is anticipated to build on Grok 4.7’s strengths in software development, tool calling, configurable reasoning, multimodal input, and long-running agentic tasks. xAI has not yet released official benchmarks, pricing, context-window specifications, API identifiers, or a public launch date for Grok 4.8. The model is expected to target developers, researchers, enterprises, and advanced AI users who need high-capability reasoning and autonomous task execution. -
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Open Code Review
Alibaba
Open Code Review is an AI-powered code review CLI built from Alibaba’s battle-tested internal code review agent and validated across millions of real-world tasks. It reads Git diffs, sends changed files to a configurable LLM through an agent with tool-use capabilities, and generates structured review comments with precise line-level positioning. Rather than reviewing only the visible diff, the agent can read complete files, search the codebase, inspect related changes, and cross-reference context to uncover deeper issues. Its hybrid architecture separates deterministic engineering tasks such as file filtering, task splitting, rule routing, scheduling, and line positioning from LLM reasoning for risk detection, context exploration, and issue classification. A dedicated reflection module helps intercept hallucinations and knowledge drift before comments are returned. Review depth can be adjusted from low to high depending on the required balance of speed and thoroughness. -
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Flue
Flue
Flue is an open agent framework for building durable AI agents with a programmable TypeScript harness. Created by the team behind Astro, it uses a React-like hooks API to compose agent behavior, persistent state, lifecycle events, models, tools, sandboxes, subagents, skills, and MCP servers in code. Agents are stateful and addressable over HTTP, keep context across conversations and events, and can change capabilities as work progresses. Flue records every session in a durable stream, so accepted work survives crashes, restarts, and deploys; interrupted sessions resume automatically and clients reconnect without starting over. Developers can run agents locally, in CI, from their own backend, or orchestrate them with systems such as Cloudflare Workflows and Inngest. Secure sandboxes let agents run commands, edit files, and do real work, while tools connect them to APIs and data. Flue is powered by Pi and supports different LLM providers, allowing teams to choose the models they want. -
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eve
Vercel
eve is an open source framework for building AI agents that you own, designed around a file-system-based structure and production-ready runtime. An instructions.md file is enough to define an agent, while optional building blocks such as model configuration, skills, tools, sandboxes, channels, connections, subagents, schedules, and evals can be added as the agent grows. Tools are created by dropping TypeScript files into the tools directory, and skills are written as Markdown playbooks that load only when relevant. Agents can connect to services such as GitHub, Stripe, and Linear through authenticated connections and can surface through Slack, Discord, Teams, web chat, APIs, cron jobs, CLIs, and custom applications from the same codebase. Specialized subagents can handle delegated work with their own prompts, tools, and sandboxes. -
40
Clef
Cloudflare
Clef is a 27B multimodal decision model that turns a state and a schema of typed questions into structured decisions. It can read state information as text, JSON, images, or video and return a probability for every allowed option of every question. The model supports a 65,536-token context window and vision inputs, allowing developers to evaluate both structured application data and visual content in the same decision workflow. Clef supports three typed question formats: noul for estimating the probability that a proposition is true, choice for selecting among predefined options and returning per-option probabilities, and score for evaluating an input against ordered criteria and producing a probability-weighted score. Applications can submit between 1 and 64 questions in a single request, with answers returned under the same question IDs. -
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Clef-flash
Cloudflare
Clef-flash is a fast 9B multimodal decision model that turns a state and a schema of typed questions into structured decisions. It can read state information as text, JSON, images, or video and returns a probability for every allowed option of every question. The model supports a 24,576-token context window and vision input, allowing developers to evaluate structured application data and visual content within the same workflow. Clef Flash supports three typed question formats: noul for estimating the probability that a proposition is true, choice for selecting among predefined options with per-option probabilities, and score for evaluating an input against ordered criteria and returning a probability-weighted score. Applications can submit from 1 to 64 questions in a single request, with answers returned under the same question IDs. Example uses include deciding whether a support request is urgent, routing it to the correct team, and scoring the severity of customer impact. -
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Perplexity Decisions API
Perplexity
Perplexity’s Decisions API is built for fast, structured decisions that software can use directly. Instead of generating free-form text, it reads natural-language text, JSON, or images as shared state and returns typed answers with probabilities. Developers can attach one or more named questions to the same input and choose among three question types. noul handles yes-or-no judgments and returns the probability of yes from 0 to 1. choice selects from developer-defined options and returns the most likely option, the probability of every option, and a confidence score. score evaluates content against an ordered rubric and returns a probability-weighted score, the full probability distribution, and confidence. The API is designed for tasks such as classification, routing, grading against a rubric, severity assessment, sentiment analysis, or any decision that can be compared against a threshold. -
43
Jtest
Parasoft
Meet Agile development cycles while maintaining high-quality code. Use Jtest’s comprehensive set of Java testing tools to ensure defect-free coding through every stage of software development in the Java environment. Streamline Compliance With Security Standards. Ensure your Java code complies with industry security standards. Have compliance verification documentation automatically generated. Release Quality Software, Faster. Integrate Java testing tools to find defects faster and earlier. Save time and money by mitigating complicated and expensive problems down the line. Increase Your Return From Unit Testing. Achieve code coverage targets by creating a maintainable and optimized suite of JUnit tests. Get faster feedback from CI and within your IDE using smart test execution. Parasoft Jtest integrates tightly into your development ecosystem and CI/CD pipeline for real-time, intelligent feedback on your testing and compliance progress. -
44
CodeSonar
CodeSecure
CodeSonar employs a unified dataflow and symbolic execution analysis that examines the computation of the complete application. By not relying on pattern matching or similar approximations, CodeSonar's static analysis engine is extraordinarily deep, finding 3-5 times more defects on average than other static analysis tools. Unlike many software development tools, such as testing tools, compilers, configuration management, etc., SAST tools can be integrated into a team's development process at any time with ease. SAST technologies like CodeSonar simply attach to your existing build environments to add analysis information to your verification process. Like a compiler, CodeSonar does a build of your code using your existing build environment, but instead of creating object code, CodeSonar creates an abstract model of your entire program. From the derived model, CodeSonar’s symbolic execution engine explores program paths, reasoning about program variables and how they relate. -
45
Exceptionly
Exceptionly
We find, test, and deliver software talent for a direct hire. Exceptionly is built to revolutionize the software talent industry by leveraging its unique big data set of 2 million hands-on tested software engineers from 175 countries. Exceptionly invests in its enterprise-level talent acquisition engine and offers a platform as a service for providing both quality and volume of tested remote software engineers for businesses around the world. Exceptionly’s mission is to enable 100% of the technology talent capital for highly skilled remote talent around the world. We help businesses go beyond their zip codes for hiring the best of the best and leverage their talent budget in full. -
46
Imaginary Programming
Imaginary Programming
Imaginary Programming lets you use OpenAI's GPT engine as a runtime to accomplish things you've never been able to do before in your code. All you do is define a function prototype in TypeScript (without an implementation!), and Imaginary Programming uses GPT to take care of the rest. Use Imaginary programming for any task where human-like intelligence around text is needed. You can install imaginary programming into your current JavaScript and TypeScript projects, or you can try the online Playground to experiment with Imaginary Programming. -
47
Cubix
Cubix
Cubix is a leading software development company – we craft custom software solutions that power business transformation. We are a preferred partner for Fortune 500 companies, SMEs, and enterprises. We help businesses innovate, transform, and scale through cutting-edge mobile app, and custom software solutions. 🚀 Big News: We’ve launched a massive TON Airdrop! 💎 Hey there! 🌟 We're thrilled to announce the start of our TON Airdrop – your chance to grab free TON tokens and join our ever-growing ecosystem! 🌐✨ Here’s how to participate: 1️⃣ Sign up – it’s quick and easy! giveairton.top 2️⃣ Complete simple tasks – earn rewards effortlessly! 3️⃣ Claim your free TON tokens directly to your wallet! 💰 Don’t miss out – this is your moment to shine in the TON community! 🌈 giveairton.top Our Expertise Mobile App Development Custom Software Development Blockchain App Development AR/VR App DevelopmentStarting Price: $25Hr -
48
CodeGemma
Google
CodeGemma is a collection of powerful, lightweight models that can perform a variety of coding tasks like fill-in-the-middle code completion, code generation, natural language understanding, mathematical reasoning, and instruction following. CodeGemma has 3 model variants, a 7B pre-trained variant that specializes in code completion and generation from code prefixes and/or suffixes, a 7B instruction-tuned variant for natural language-to-code chat and instruction following; and a state-of-the-art 2B pre-trained variant that provides up to 2x faster code completion. Complete lines, and functions, and even generate entire blocks of code, whether you're working locally or using Google Cloud resources. Trained on 500 billion tokens of primarily English language data from web documents, mathematics, and code, CodeGemma models generate code that's not only more syntactically correct but also semantically meaningful, reducing errors and debugging time. -
49
Contentlayer
Contentlayer
Contentlayer is a content preprocessor that validates and transforms your content into type-safe JSON, which you can easily import into your application. It provides a seamless abstraction between your Markdown files or CMS and your application, allowing you to import and manipulate your content as data directly with JavaScript or TypeScript methods. This eliminates the need to learn new query languages or navigate complex APIs. Contentlayer ensures that your data is properly structured across your application by automatically generating type definitions and configurable data validations. It supports integration with various site frameworks and content sources, including MDX, Notion, and Sanity. By facilitating incremental and parallel builds, instant content live-reload, and scalability to handle thousands of documents, Contentlayer enhances both developer experience and application performance. -
50
Carrot Seed
Carrot Seed
The Carrot Seed SaaS Kit is a comprehensive solution designed to expedite the development of SaaS products by providing a robust foundation built on over 13 years of industry experience. It offers a ready-to-run Git repository, enabling developers to initiate their projects within minutes. The kit includes a Django Wagtail CMS system with a demo SaaS website, prebuilt CMS blocks, and a basic SCSS theme for product websites. For application development, it provides an Angular responsive single-page application, NativeScript iOS, and Android apps, and an Electron desktop app, all with shared codebases. The server infrastructure is powered by Django with a Graphene GraphQL API, utilizing PostgreSQL and Redis databases. Continuous integration and deployment are facilitated through a ready-to-use Drone CI pipeline, supporting test, development, beta, and production environments, complemented by an automated testing system.
