Product manager working with an AI agent on a complex deliverable
Chat with the AI employee and watch its reasoning unfold live. You see how it thinks, not just what it outputs.
Chat with Live Reasoning
Watch your employee think, plan, and decide in real time with streaming responses you can stop or redirect mid-sentence.
Chat is the primary way you work with your AI employee. Messages stream in real time so you see the response forming word by word. More importantly, you see the reasoning: what the employee is thinking, which tools it is calling, what decisions it is making, and why. This is not a chatbot that spits out a block of text. It is a colleague showing their work.
Imagine asking your employee to research competitors in your space. You watch it decide to search the web, pick specific queries, read through results, discard irrelevant pages, extract pricing data, and start composing a summary. If it heads in the wrong direction, you stop it mid-sentence and redirect. "Focus on European competitors only." It adjusts immediately and continues.
The chat supports rich media: images, files, tables, code blocks, and structured documents appear inline. Your employee can share a generated image, attach a spreadsheet, or display a formatted report directly in the conversation. Everything stays in one thread, and the full history is searchable.
Real-Time Streaming with Visible Reasoning
Every conversation with your AI employee streams in real time, word by word, so you always know what is happening. Unlike black-box AI tools that return a finished answer with no explanation, Sistava shows the agent's full reasoning process as it works through your request.
Visible reasoning means you can catch mistakes before they compound. If the agent starts heading in the wrong direction, you see it immediately and can redirect mid-sentence without waiting for a wrong answer to finish.
Tool Usage You Can Watch and Control
When your AI employee uses a tool, like running a search, calling an API, or reading a file, you see exactly which tool was called, what arguments were passed, and what came back. There is no guessing about what the agent actually did.
This transparency turns the agent into a collaborator rather than a black box. You can stop the agent at any point, override a tool call, or redirect the task entirely without losing context or starting over.
Built for Iterative, Back-and-Forth Work
Sistava chat is not a one-shot prompt interface. It supports deep, multi-turn conversations where you refine, push back, add context, and guide the agent across dozens of exchanges.
Whether you are drafting a proposal, researching a market, or debugging a workflow, the AI agent maintains full context throughout the session. Each message builds on the last, and the agent adapts in real time as requirements evolve.
Use Cases
Support agent resolving multi-step customer issues in real time
The AI employee reasons through the problem, takes action, and reports back, all within the chat thread.
Analyst using an AI agent to work through a research question
Ask, watch the agent reason step by step, and course-correct in real time if it heads the wrong direction.
Executive getting a quick decision-support answer from their AI employee
The agent surfaces the reasoning behind its recommendation so you can trust the answer, not just accept it.
Comparison
| Before | After |
|---|---|
| You get an answer but have no idea how the agent reached it. | Live reasoning lets you watch every step of the agent's thinking in real time. |
| Errors are only visible after the agent finishes, too late to catch. | See the reasoning as it happens and redirect before the agent goes wrong. |
| Chat feels like a black box, input in, output out. | Transparent reasoning makes collaboration feel like working with a colleague. |
| You have to trust the output without any way to verify it. | Follow the reasoning chain and validate the logic before acting on the result. |
FAQ
Can I stop the AI agent while it is in the middle of a response?
Yes. You can stop the agent at any point during a streaming response and redirect it with a new instruction. The agent picks up with your new direction without losing the conversation context built so far.
What does "visible reasoning" mean in practice?
Before giving you an answer, the AI employee works through a chain of thought you can read in real time. You see how it interpreted your request, what it considered, and why it chose a particular approach.
Does the chat support long, complex tasks or just quick questions?
Both. The chat interface handles everything from quick lookups to multi-step research and execution tasks that take several minutes. The agent maintains context across the full conversation, no matter how long it runs.
Can I see which tools the AI employee used during a conversation?
Yes. Every tool call, including the input arguments and the result, is shown inline in the conversation. You get a full audit trail of exactly what the agent did to produce its answer.
Can I see what my AI agent is doing while it works, not just the final answer?
Yes. The chat interface streams live reasoning and shows each tool call as it happens, so you can follow the agent's thinking in real time. There is no black box, every step is visible.
Watching the agent reason through a complex research task in real time changed how I think about AI. I could see exactly why it made each decision. That kind of transparency is rare.