SparkAi
Engineering partnership · Secure AI Agents

Secure AI chat and agents

One secure workspace for models, agents, tools and workflows, governed by role.

Give every team AI that respects your data, roles and rules.

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Roles and access screen with a permission matrix across five roles, a data sensitivity ceiling for each role and a role detail panel.
Secure AI Agents

See it in action

An enterprise AI platform with role-based access at its core. Teams chat with many models, pick agents and tools from shared marketplaces, hand long tasks to a Cowork module that plans, delegates and checks its own work, and run workflows and autonomous agents.

  • 0marketplaces
  • 0ways to chat
  • 0modules
Roles and access screen with a permission matrix across five roles, a data sensitivity ceiling for each role and a role detail panel.
Role-based access control

01Role-based access

Enterprise roles decide who can use which models, agents, tools and data, so AI adoption grows without losing control.

  • Roles
  • Permissions
  • Audit
Capabilities

Everything in the platform

6 modules, built from scratch for our partner and run in production by our team.

01

Role-based access

Enterprise roles decide who can use which models, agents, tools and data, so AI adoption grows without losing control.

  • Roles
  • Permissions
  • Audit
  • Enterprise role-based access system
02

Marketplaces

Shared catalogues of language models, ready-made agents and functions. Teams pick what they need and publish their own.

  • Models
  • Agents
  • Tools
  • LLM model marketplace
  • Agent marketplace
  • Function and tool marketplace
03

LLM chat

Chat that knows how sensitive a conversation is, calls tools when needed, and in AutoPilot picks the right model and tools for each question.

  • Sensitivity aware
  • Tool calling
  • AutoPilot
  • Sensitivity awareness at different levels
  • Tool calling
  • AutoPilot, which selects models and tools automatically
04

Cowork

Hand over multi-step work. Cowork plans the task, runs sub-agents with tools and skills, checks each result and the final answer, and manages memory and context throughout.

  • Planning
  • Sub-agents
  • Self evaluation
  • Agentic orchestration
  • Looped agent
  • Agentic planning
  • Agentic execution
  • Tool calling
  • Skill calling
  • Sub-agent execution
  • Self evaluation of each sub-agent and of the overall response
  • Memory management
  • Context management
05

Workflows and autonomous agents

Build AI workflows that run on a schedule or a trigger, and deploy autonomous agents that work in the background and report back.

  • Workflow builder
  • Triggers
  • Autonomous runs
  • AI workflow execution platform
  • Autonomous agent execution platform
06

Team chat

Colleagues message each other directly or in groups in the same secure workspace, and share files and AI answers into the conversation.

  • Direct messages
  • Group chats
  • Shared answers
  • User to user chat
  • Direct and group conversations
  • Share files and AI answers with colleagues
Delivery and operations

How we built and run it

  • Runs in the cloud, on premise or as a hybrid, with the workspace behind the customer's own sign-in.
  • Prompts, files and agent memory stay in the customer environment. Sensitive requests are kept on private models.
  • Roles decide which models, agents, tools and data each person can use, and runs are logged for review.
  • Cloud models, self-hosted models or both, chosen by data sensitivity level.
  • Built from scratch by SparkAi, which still runs releases, monitoring and new features.
Engineering partnership

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