Core layer
Personal assistant for each teammate
Every operator keeps private working memory, personal defaults, and teammate-level assistance instead of competing for one shared chat window.
Managed pilots for software teams
Give every teammate a personal assistant and your company one shared operational brain.
Automa orchestrates software delivery across chat, voice, Slack, dashboard, and routines so the team keeps moving without constant re-prompting, re-briefing, and context loss.
Personal
1 assistant
per teammate with private memory and defaults
Shared
1 operational brain
for company context, work state, and knowledge
Commercial
Pilot-first
managed hosting now, self-hosted for higher-trust deals
Talk with us about Automa
Share your work email and a little context. We will follow up with pilot details and next steps.
Why this matters now
AI makes implementation cheap. The leverage moves into direction.
TavernScribe is useful proof because the team could build quickly. The bigger unlock was keeping context, task boards, and routines unified so people could direct parallel execution instead of carrying every implementation detail themselves.
"The real bottleneck is no longer raw creation capacity. It is how many projects a founder can care about deeply enough to push across the line."
That is the shift Automa is built for. We help your team move into a stronger director role, where each person can manage AI agents, steer execution, and keep more projects moving without becoming the implementation bottleneck again.
In practice, that means users spend most of their time in the planning phase at the task level, shaping work, reviewing what should happen next, and letting agents carry more of the implementation and review load.
People can reach that system through Slack, live voice, dashboard chat, and other interfaces, so Automa behaves more like an actual teammate than another isolated tool.
Platform
Automa is built around three promises.
The commercial launch work is focused on software teams, not a generic executive concierge. The product promise is simple: each teammate gets a personal assistant, the company shares one operational brain, and routines keep work moving without constant prompting.
Core layer
One shared operational brain
Company context, project knowledge, and active work stay connected so the team stops re-explaining the same state across meetings, tools, and prompts.
Core layer
Routines that keep work moving
Recurring work, follow-ups, summaries, and coordination loops can run automatically instead of depending on who remembered to ask.
Features
The operating layer that makes fast execution usable.
Automa is not one feature. It is the system that connects context, planning, task boards, routines, interfaces, and AI execution so your team can actually use modern tools inside the business model instead of just demoing them.
That includes full planning phases, automated PR and security reviews, and agent access to the same engineering surfaces people use to investigate and ship work.
It also means Automa can live inside Slack at different levels of your organization, connect to your calendar, ingest meeting context through Fathom, and offer live voice agents you can talk to in context like one of your team members.
Feature set
Planning-first task boards
Most interaction happens at the task level during planning. Automa gives users one place to shape the plan, assign ownership, define next actions, and keep execution aligned before work fans out.
- task-level planning before implementation starts
- shared visibility across people and agents
- clear ownership, sequencing, and handoff state
Feature set
Routines that keep momentum alive
Turn recurring follow-up, summaries, approvals, and operational loops into routines so the business keeps moving between meetings.
- repeatable operating cadences
- less follow-up drift
- bias for action built into the workflow
Feature set
Shared context and memory
Automa keeps one coherent operating picture across conversations, tasks, knowledge, and execution so teams stop re-briefing the same work and can ask better questions from the same source of truth.
- workspace and company context
- less context switching
- better continuity across interfaces
Feature set
Automated PR and security reviews
Review automation is built into the operating flow, so pull requests and security checks do not rely on someone manually remembering the review pass every time.
- automated PR review loops
- security review as part of the task flow
- human oversight where judgment matters
Feature set
Personal assistants for each teammate
Each teammate gets private memory, defaults, and assistance while still benefiting from the shared organizational brain.
- personal working context
- team-wide coordination without losing personal flow
- less competition for one shared chat
Feature set
Slack-native teammate access
Automa can show up as a teammate inside Slack so people across your organization can interact with tasks, planning, and execution from the interface they already use every day.
- works inside the team's existing Slack flow
- access can reach different levels of the org
- same context path without switching tools
Feature set
Calendar-connected meeting capture
Automa can connect to your calendar and automatically ingest meeting context through Fathom so decisions, notes, and follow-up work enter the operating layer without manual recap.
- calendar integration for meeting visibility
- automatic meeting ingestion through Fathom
- follow-up context captured without another summary pass
Feature set
Live voice agents
You can talk to Automa over voice like one of your teammates, ask questions in live context, and direct work without dropping down into a separate control panel.
- natural voice interaction
- live context while you talk
- direction and follow-up like a real teammate
Feature set
Engineering-grade AI execution
Automa can route work into Claude, Codex, APIs, and human approvals while giving agents the same working context engineers use, including read access to databases, logs, and errors.
- faster implementation throughput
- humans stay in director mode longer
- read access for investigation and building context
- shared responsibility across teams and clients
Move team members from implementation to direction
When AI makes implementation cheaper, the leverage shifts into deciding, sequencing, and steering the work. Automa gives the team one place to direct that motion.
Turn context sprawl into one operating layer
Slack, voice, dashboard chat, knowledge, task boards, and routines share the same context path so important work does not fragment across surfaces.
Create a bias for action with boards and routines
Unified task boards make ownership visible, and routines keep follow-up moving so next steps do not wait on another meeting or another re-brief.
Keep humans in the loop without slowing everything down
Approvals, stakeholders, and client visibility stay inside the system instead of becoming side-channel work that breaks the flow.
Execution surface
Users plan at the task level while agents work with engineering context.
Automa is meant to be used where the work is actually managed: planning, review, follow-up, and execution. Agents can inspect code, logs, errors, and read-only database context so they can answer questions and support building with the same visibility an engineer would expect.
That same system can show up in Slack as a teammate and over live voice, and it can pull context in from calendar-linked meetings through Fathom, so access is available where different people in the organization already work.
Work across the interfaces your team already uses
- Slack teammate integration
- calendar integration
- Fathom meeting ingestion
- live voice agents
- dashboard chat
- Telegram
- MCP for coding agents
Plan and review at the task level
- full planning phases around each task
- unified task boards
- automated PR reviews
- automated security reviews
- human approvals and notifications
Operate with engineering-grade context
- Claude and Codex task harnesses
- workspace-scoped knowledge retrieval
- read access to databases for questions and build context
- logs and error visibility
- routine execution
- organization and workspace separation
- managed hosting first
- self-hosted option for higher-trust teams
- manual pilot onboarding with human oversight
Built Inside LOJI
Created for our own workflows, refined with clients, now opened to the public.
LOJI product engineers built Automa to run our own operating model. We used it in client delivery to build faster and deliver value at astronomical scale by shifting engineers into coherent directors inside the system, and by sharing responsibility across LOJI, our clients, and the people doing the work.
Now we want to offer that same leverage to your organization and your personnel, so you can take advantage of the tools that are now available to every business model.
We still want an engineer on your team keeping tabs on the system. If you do not have that person in-house, LOJI can partner with you to help you use Automa well.
Built inside LOJI first
Automa was created by LOJI for its own workflows, where product engineers needed a stronger operating layer for context, tasks, routines, and AI execution.
Used with clients to deliver at larger scale
We used it inside client work to build faster, coordinate better, and deliver value at a scale that would have been harder to manage with traditional operating habits.
Now being opened to the public
What started as an internal operating advantage is now something we want to offer to your organization and your people so more businesses can benefit from the same leverage.
First user story
TavernScribe shows how teams move from implementation to direction.
AI made it possible to build fast. Automa made that speed usable by unifying context, task boards, and routines so the team could operate with a bias for action and manage AI agents from a more director-level position.
Read the storyBuild speed stopped being the constraint
TavernScribe could move from idea to working system fast enough that implementation no longer needed to consume the entire team.
Unified context let everyone direct from the same map
Shared context across conversations, tasks, and knowledge reduced re-briefing and made parallel execution easier to steer.
Boards and routines created a bias for action
Unified task boards and recurring routines kept ownership visible, follow-up moving, and the business pointed toward the next decision.
Compare
Why Automa instead of another AI or automation tool?
The short version: Automa is meant to operate the software team, not just answer prompts, generate code, or move fields between apps.
Automa vs ChatGPT
ChatGPT is a strong conversation surface. Automa is the operating layer around the work: shared memory, team context, routines, approvals, and project boundaries.
Automa vs Copilot
Copilot helps an individual developer produce code. Automa coordinates the broader software team across tasks, knowledge, stakeholders, and multi-project execution.
Automa vs Zapier
Zapier automates deterministic handoffs. Automa adds company memory, AI reasoning, teammate context, and human checkpoints around the process itself.
Automa vs n8n
n8n gives you a flexible workflow engine. Automa packages orchestration, context, and software-team collaboration into a product instead of a blank automation canvas.
Start here
Tell us where the orchestration is breaking down.
We are using founder-led paid pilots to help software teams move from prototype energy to production reality. If you want your team spending more time directing AI agents and less time buried in fragmented implementation, start with your email and we will get in touch.
Request more information
Drop your work email and a short note about your team, workflows, or AI-agent goals. We will follow up directly.