Delegate reports, research and follow-ups to AI that works with your documents and tools. Set the goal, give it access, and review the decisions that need your judgment.
A workflow can continue, request a human decision or stop according to its configured policy.
An AI agent is an assistant that can use tools to carry out a task. In Altherium, you give it a goal, the material to work with and the access it needs.
“Read this week’s customer feedback. Group recurring problems and show me the evidence before I choose priorities.”
Needs: feedback files or a connected source.
A synthesis of themes, links back to the source material and open questions. Your team decides what belongs on the roadmap.
“Prepare the weekly project update from our notes. Flag blockers and leave a draft for me to review.”
Needs: project notes; a connected tool if you want delivery.
A draft with progress, blockers and next steps. Once the process works, schedule it and add a checkpoint before delivery.
“Review this pull request against our rules. Explain the risks and keep the evidence so a person can decide.”
Needs: repository access and your review criteria.
A review with findings and supporting context. Use workflow steps, permissions and policy gates when you need a repeatable process.
These examples show possible workflows, not preconnected demos. Results depend on your sources, model and configuration.
Projects, files, knowledge and memory.
Durable workflows, schedules and checkpoints.
People, service accounts and scoped permissions.
The pieces of daily work, in the same place.
A project brings together files and, optionally, a Git repository. Agents can draw on documents, skills and scoped memory. Teams share work through the board and keep conversations connected to the project.
Define steps and dependencies, launch a run or schedule it with a cron. Durable execution preserves progress so a paused workflow can resume. Review outputs, errors, tokens and cost by step.
People and service accounts have distinct identities. Teams have their own automation account; permissions and connections determine what each actor can access. A service account can administer a team, without becoming a global administrator.
Configure policies using signals, rules and a rubric. At a workflow gate, the decision can allow progress, ask a person or block it. Inspect the evidence behind that decision.
Understand the controlsUse shadow mode to limit actions while you evaluate the workflow.
Inspect gate decisions and compare draft policies against recorded decisions.
Use approvals and brakes to control when agents and workflows can act.
Start with the connections you need. Add infrastructure when it helps.
Connect supported providers or serve local models with llama.cpp. Select the model for the task and inspect usage through the platform.
Use MCP servers to bring external tools into agents. Expose Altherium operations through its own MCP server to other clients. Slack connects conversations to the same platform.
Run the control plane in a container, with SQLite or PostgreSQL. GPU nodes are optional for local inference and communicate with the plane over mutual TLS.
Walk through a task from its first instruction to a reviewed result. No architecture diagram required.
Take the walkthroughCompare hosting, models, integrations and controls. See where Altherium fits and where another product may suit you better.
Open the comparisonConnect a tool, give an agent context and decide what needs your approval. Build from there.