Assembled combines AI agents with advanced workforce management to give support teams the speed, flexibility, and control they need to excel. Our platform streamlines staffing for both in-house and outsourced teams, delivers forecasts with over 90% accuracy, and automates more than half of customer conversations. Whether it’s chat, email, or voice, Assembled orchestrates every interaction, allocating work between AI and human agents in real time. Leading brands like Stripe, Canva, and Robinhood rely on Assembled to boost performance and turn support into a growth driver. Key capabilities include scheduling, forecasting, live performance monitoring, vendor management, AI-powered chat, voice, and email agents, plus an AI Copilot that provides instant guidance, suggested responses, and rapid action tools for agents.
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Forethought is the most advanced generative AI agent for customer support and your 24/7 AI team member. Trained on your unique data sets and upholding the highest security protocols, Forethought delivers natural conversations through AI and eliminates inefficiencies to improve response times, resolution rates, and customer satisfaction scores at every interaction.
- Add an AI Agent that is a 24/7 team member, reducing workload so your team can focus on delivering exceptional support.
- Only Forethought ingests historical and current ticket data for AI specific to your business needs to deliver a personalized experience.
- We're not just about meeting privacy standards – we're setting them, to keep you and your data secure every step of the way.
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Kimi K3
Kimi K3 is a large-scale AI model from Moonshot AI designed for advanced reasoning, software engineering, visual understanding, agentic workflows, and knowledge work. The model is built with 2.8 trillion parameters and uses Kimi Delta Attention, a hybrid linear attention design created to support long-context intelligence. It also includes Attention Residuals and a native 1 million token context window, giving developers room to work with large files, repositories, documentation sets, transcripts, and enterprise knowledge bases. Kimi K3 always runs with thinking mode enabled and currently supports maximum reasoning effort by default. Developers can access the model through Moonshot’s OpenAI-compatible API using Python, cURL, and the OpenAI SDK. The API supports standard chat completions, streaming output, structured JSON Schema responses, partial continuation from a prefix, custom tool calling, required tool choice, and dynamic tool loading. Kimi K3 also supports vision inputs, including local images encoded as base64 and video files uploaded through the file API. Automatic context caching helps repeated long-prefix workflows become more efficient without requiring manual cache IDs or extra cache parameters. By combining long context, visual understanding, tool use, structured output, and advanced reasoning, Kimi K3 is built for developers creating sophisticated AI agents, coding systems, research tools, and enterprise applications.
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Kimi K2.7 Code
Kimi K2.7 Code is a Moonshot AI coding model built to help developers handle software engineering, code generation, debugging, and agent-based development workflows. It focuses on long-horizon coding tasks, where an AI assistant needs to understand goals, work across many files, and complete multi-step development work. The model builds on the Kimi K2.6 architecture and is described as improving agentic capabilities while reducing thinking-token usage by about 30% compared with K2.6. Kimi K2.7 Code offers a 256K context window, which helps developers work with larger repositories, longer prompts, and more detailed project instructions. It can be accessed through Kimi Code, Moonshot’s API platform, and third-party model providers such as Together AI. The model also supports OpenAI- and Anthropic-compatible APIs, making it easier for teams to test it as a replacement or addition to existing coding assistant workflows. Developers who want to self-host or experiment with the model can access it through Hugging Face, where deployment guidance references vLLM, SGLang, and KTransformers. Kimi K2.7 Code is especially relevant for teams interested in open-source coding agents, long-context software tasks, and tool-integrated development. While some third-party commentary notes that benchmark claims should be reviewed carefully, the model is positioned as a strong option for developers seeking flexible, agentic coding support.
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