Your AI agents work
on your laptop
.
They're useless to everyone else.
The Problem
Everyone has AI workflows.
Nobody can run them for a team.
The Individual
Your sales rep's prospect research is lethal. Your analyst's data pipeline runs 3x faster than anyone else's. Your engineer's code review catches bugs nobody else sees.
Trapped on one laptop.
The Framework
CrewAI, LangGraph, AutoGen — built for an era when you coded agents line by line. You've traded your working prompts for lock-in inside legacy abstractions. Modern agents are prompts, skills, and tools — powered by models smart enough to use them.
Plumbing, not products.
The Dream
A platform that takes what already works for one person, runs it safely for many, measures it, and makes it better automatically.
We built it.
How It Works
Five steps from laptop to
production agent system
This isn't a pipeline builder. It's a platform that runs your agents, judges them, and makes them better.
Install
Pick a Starter Kit or import your own skills, prompts, and scripts.
Run
Execute with budget, policy, and a live task graph. No infra to manage.
Evaluate
Judge the run against Goals. Gates pass or fail. Quality scores are recorded.
Improve
AI proposes a governed ChangeSet. You review and approve the improvement.
Compare
Re-run the new version. See the delta. Watch your agents get better.
Why Nicia
Not another framework. Not another single-vendor loop.
The platform you bring to the work.
| Build from scratch | Personal use | Managed by model vendor (Claude Managed Agents, etc.) | Nicia | |
|---|---|---|---|---|
| Starting point | New code and orchestration logic | Files on one laptop | Claude-native SDK | Your existing skills, prompts, scripts |
| Execution | Your infra | Your laptop | Managed sandboxes (Claude only) | Managed sandboxes, any model, fast by default |
| Speed | Your code's latency | Whatever the laptop runs | Long-running autonomous sessions | Right-sized models per step. Finishes fast. |
| Coordination | Your code | Single agent | Claude multi-agent (research preview) | Prompt-driven task graphs |
| Context | Build it yourself | Whatever you paste in | Model memory + tool calls | Distilled sources, artifacts, prior decisions carried into every run |
| Evaluation | Build it yourself | Informal | Self-evaluation loop | Goals, evaluations, comparisons |
| Oversight | Your logging | Watch the terminal | Execution tracing | Audit trail, budgets, approval gates with named responders |
| Improvement | Manual iteration | Ad hoc | Autonomous self-evaluation loop | Evaluation-driven, governed, human-approved ChangeSets |
| Scaling | Your problem | Doesn't | Within the Claude ecosystem | Reusable across teams, models, and workflows |
Build from scratch: CrewAI, AutoGen, LangGraph, Temporal+LLM • Personal use: Claude Code, Aider, Cursor • Managed by model vendor: Claude Managed Agents
What Makes Nicia Different
The things no other
platform does.
Agents that get better
after every run.
Other platforms run your agent and hand you a log file. Nicia evaluates every run against your Goals, diagnoses what went wrong, and proposes a specific, reviewable improvement.
You approve the change. A new version is created. Next run scores higher. That's not a feature — it's a fundamentally different kind of platform.
Stop reinventing.
Use the best your org has.
Your best engineer has a code review skill that catches 40% more bugs. Your top analyst has a data-cleaning workflow that runs 3x faster. Right now, those live on individual laptops.
Nicia turns individual excellence into organizational capability. Package the best skills, share them across agents, and let every team member benefit from the best work anyone has done.
Define what good looks like.
Grade every run.
Goals are versioned success contracts with hard gates and quality scores. They don't just tell you if an agent ran — they tell you if the result was actually good.
Run the same agent against the same Goal across versions and watch a leaderboard form. Your agents compete against your standards, and the standards win.
Humans in the loop, by default.
When the work has to be right, not just finished.
Nicia routes work to named people when a workflow needs their judgment. Handoffs. Approval gates. Rubric-driven review. Not an afterthought bolted onto an autonomous loop — a first-class primitive, designed for the workflows that can't go fully autonomous. Which, in the enterprise, is most of them.
Other platforms treat human oversight as a safety net. Nicia treats it as the reason the work gets done right in the first place. Every run that needs a human gets one. Every approval becomes part of the record. Every correction teaches the next run what "good" looks like.
Your agents reason over the
right context, every run.
Artifacts, prior decisions, distilled sources. Nicia carries the right context into every run — versioned, diffable, and improving as your agents learn what matters. Files the agents create. Files your users upload. Files synced from Google Docs, Notion, and the other places knowledge lives. All in one place, with one lineage, at the organization level.
Not just a memory store. A working model of your operation. When someone in marketing edits the brand voice document, Nicia shows you the diff and lets you decide when your agents adopt the change. When a workflow needs a pricing sheet, you don't rewire credentials for every user — one person or an IT admin syncs the source and the whole team's agents use it.
Fast by default.
Right-sized by design.
Nicia routes each step to the model that's actually right for it. Tiny models for bulk work. Big models for hard reasoning. Agents that finish in seconds, not minutes. Sandboxes that spin up fast, because waiting breaks flow.
Every developer knows the feeling of Claude Code defaulting to Opus for a task Haiku could nail in thirty seconds. Your team feels it too. Nicia picks the right size model per step — so the work finishes in the time the work should take.
And the foundations that make it all possible
Emergent Task Graphs
No DAGs to author. Agents create tasks dynamically. The graph is what happened, rendered in real time.
Policy Governance
Budgets, tool allowlists, model restrictions, network egress rules. Start permissive, tighten over time.
Complete Audit Trail
Every tool call, LLM invocation, network request, and approval decision. Recorded, queryable, tamper-evident.
Any model, any provider
Route per step via AI Gateway. BYOK. Compliance logging. Built for teams that can't bet their workflow on one vendor's loop.
Developer Experience
One API call to launch.
Full control when you want it.
Trigger runs, stream live events, evaluate against goals, propose improvements, and compare versions. All through a clean REST API.
# Launch an agent run
curl -X POST /v1/agents/sales_outreach/run \
-H 'Authorization: Bearer na_...' \
-d '{
"input": { "leads": "artifact://leads.csv" },
"budget_usd": 5,
"goal_ids": ["goal_q1_outreach_quality"]
}'
# Response: run created, evaluation scheduled
{ "run_id": "run_47", "status": "active" }Your agent is live.
Import your skills, prompts, and scripts. Launch with one API call.
It rewrites itself.
Evaluation runs automatically. AI proposes its first improvement.
Your team's best work. Automatic.
Governed, measured, and getting better with every run.