Paroksh · the Cisely agent

One assistant, from the first question to the running system.

Paroksh works across both pillars of Cisely. It builds your business context with you in Context Management. Then it builds the software from it in the Software Factory. You keep the vision and the judgement. Paroksh does the work.

Request a demo Where it stops

Across both pillars

One agent, so nothing is lost at the handover.

The agent that wrote down why your business exists is the agent that builds the software for it. The reasons travel with the work.

Pillar 1 · Concise

In Context Management

It starts from an empty workspace with a short interview, a few questions at a time.
It researches public sources, and marks what it inferred.
It reads the documents, images and PDFs you attach.
It drafts your mission, beliefs, strategy, personas and expectations.
It shows you each draft before it writes it.

Explore Context Management

Pillar 2 · Precise

In the Software Factory

It checks that the context is ready before it writes the application.
It writes the application in Vishwakarma, and uses the checker’s explanations.
It takes solved problems from the blueprint catalogue before it invents one.
It runs the application live, in an isolated session with its own preview.
It ends each session with a proposed change, for your team to review.

Explore the Software Factory

Where it stops

You decide what becomes authoritative.

Paroksh can research, draft and build, but consequential changes still follow explicit review and approval rules. These are the boundaries built into the workflow.

AI-generated context stays in draft: Review, correct and activate what you agree with. Until then, the content remains a proposal and is not treated as approved context.
Questions stay focused: When Paroksh needs structured input, it uses a form with no more than three questions at a time.
Human decisions block progress: If work depends on your judgement, Paroksh pauses and presents a decision that must be answered before the task can continue.
Missing rationale is reported: If work has no approved expectation or business reason behind it, Paroksh reports the gap instead of inventing one.
Unattended does not mean unsupervised: When nobody is present, a consequential action waits for an operator. The approval requirement belongs to the operation and applies to every caller.
It reports what happened, not what it expected: Failures, skipped steps and unverified results remain visible in the handoff instead of being summarised away.

Governance

Governed like an employee with a manager.

The boundaries above are not a promise in a prompt. The platform enforces them, and keeps the record.

Risky actions wait for a person: A risky action stops until a person decides. Cisely keeps the decision, the approver and the saved state, and an approved action runs once.
Confirmations are permanent: Nobody can delete a confirmation. It is the record that a person allowed an agent a real effect.
Every turn is on the record: Cisely records every turn, every tool call and every model call, with its model, its tokens and its cost.
As you, never as itself: Every write runs as the signed-in member, through the same permission checks as a manual action.

Your choice of model

Use the model you trust, or the subscription you already pay for.

Your model provider: Connect Anthropic, OpenAI, Google, AWS Bedrock or a model router. You can revoke a connection at any time.
Your own subscription: Run Paroksh on Claude Code with a Claude subscription, or on OpenAI Codex with a ChatGPT plan.
The same gates either way: The review gates, the audit and the project record do not change with the model you choose.

Prefer the AI assistant you already use? Connect it to Cisely through MCP. It works on the same model, under the same permissions. Connect your own assistant.

What it remembers

Sessions end. The project record continues.

The journal persists between sessions: A session ends, but decisions, lessons and work history remain in the project journal.
A session begins by reading the last one: A new session can read what was attempted, what changed, what was learned, what is blocked and what should happen next.
Handoffs are explicit: Large tasks are left with checkpoints and a concrete next step so another session can continue without relying on hidden memory.

You keep the vision. Paroksh does the work.

Start with a short description of your business. Review what Paroksh drafts, correct what is wrong and approve what is useful. The agent structures and drafts. You decide what is true.

Request a demo The whole platform