LabsForward-deployedengineers for AIthat ships.
Novaric Labs embeds senior engineers with your team. We learn the workflow, build inside the stack you already run, and leave you with systems your people operate — not a deck and a demo.
Three systems. Deploy in any order.
Most clients start with one and end up using two. Enablement builds the capability, Automation puts it to work, and the Lab turns what we learn in the field into products.
AI Enablement
For teams who want to build, not outsourceWe stand up the foundation your team needs to use AI safely, then teach them to build on it themselves. Model access, guardrails, evaluation, and the working habits that separate a pilot from a practice.
- AI workflow audit with a ranked build list
- Model access, policy, and cost controls
- Evaluation harnesses for your use cases
- Hands-on training for engineers and operators
- Internal tooling and prompt libraries
- Vendor and platform selection
Automation
For operations that run on queues, inboxes, and documentsWe design agents that do the work — routing, drafting, reconciling, escalating — inside your CRM, ticketing, email, and data. Every high-stakes action runs through an approval gate you control, and we stay until it runs without us.
- Multi-step agents with human approval gates
- Integration with the systems you already run
- Document intake, extraction, exception handling
- Monitoring, logs, and a kill switch on day one
- Fixed-scope pilots that become managed retainers
- Code handed over, not held hostage
Incubator Lab
Where field patterns become productsThe same problems show up across clients. When one is worth solving properly, we build it as a product in the Lab — funded by our services work, shaped by real operators, and open to partners who want to co-build or be first to run it.
- Products born from repeated client patterns
- Design partners get early access and a say in the roadmap
- First product: an agentic harness for property management
- Co-build and revenue-share for the right partner
Is AI right for your workflow?
Five questions, one candid read — no email requiredAnswer five quick questions and get a candid, AI-generated assessment of where automation fits — and where it doesn't — for your operation. Your answers are sent to Claude to generate a one-time assessment. Nothing is stored.
Powered by Claude
Takes about a minute.
Five questions about your industry, your team, and the workflow that hurts most.
How an engagement runs.
Forward-deployed means we work where the work happens. Short scoping, fast embed, and a handoff that leaves your team in control.
Scope the workflow
One working session on the process costing you the most. You get a written scope, a fixed price, and a straight answer on whether AI fits.
Embed with your team
An engineer sits with the people doing the job, maps the real flow including the workarounds, and connects to your systems read-only.
Ship into production
Agents go live behind approval gates. We tune on real volume, widen the gate as trust builds, and instrument everything.
Hand off or retain
Your team gets the repo, the runbook, and the training to operate it. Keep us on a managed retainer or run it yourselves.
The Lab turns repeat problems into products.
Every engagement leaves us with the same observation: some workflow breaks the same way at every client, and nobody has solved it properly. When a pattern shows up often enough, it graduates into the Lab and gets built as a product.
Client work pays for it. Operators shape it.
The Lab isn't a research group or a side bet. It's funded by the services business, which means a product doesn't have to raise a round — it has to work for the people who asked for it. Design partners are in the room before the first line of code, and they keep a say in where it goes.
- Patterns, not betsA problem gets promoted only after it has cost several clients real time and money
- Funded by the fieldworkServices revenue pays for the build, so the roadmap answers to operators, not a term sheet
- Design partners from day zeroThe people who'll run it help scope it, test it on real volume, and set the order of work
- Co-build or first to runPartners can take early access, a seat on the roadmap, or a revenue share in what gets built
Now in buildFirst out of the Lab: an agentic harness for property management — pre-launch, and taking design partners.
- Pattern spottedRecurringThe same workflow breaks the same way at a third client, and the workaround is always manual.
- Worth building?GatedA pattern only graduates if nobody has solved it properly and operators say it's worth the trouble.
- Built with partnersFundedServices revenue pays for the build. Design partners scope it and run it on real volume.
- Runs in productionShippedIt leaves the Lab as a product, with the partners who shaped it first in line to run it.
Have a product the Lab should build?
If you run an operations-heavy business and keep hitting the same wall, we want to hear about it. The best Lab products start as a client problem nobody has solved well.
Next in the pipeline
The property management pattern — high volume, rules-driven, document-heavy — repeats in financial services back office, healthcare admin, legal, and logistics. That's where we're looking next.
Operators who happen to build AI.
Plenty of teams can call an API. Fewer understand what it takes to run automation inside a business that can't afford to break. That's the gap we work in.
Production, not demos
We ship systems that survive real volume, edge cases, and the messiness of live operations. A slick prototype isn't the goal.
Human-in-the-loop by default
Agents handle the volume; people keep the decisions that carry risk. Approval gates are designed in from the start, not bolted on.
We integrate, we don't replace
Your team keeps the tools they know. We connect AI into the systems you already run instead of forcing a migration nobody asked for.
You own what we build
The code, the prompts, the evals, the runbook. Forward-deployed means we leave your team able to run it without us.
“The hard part was never the model. It was making automation that operations teams actually trust enough to run every day.”
Tell us about the workflow that's costing you the most.
We'll come back with a straight answer on whether — and how — AI fits, and a fixed-price scope if it does. Founding engagements in Q4 2026 get priority on our engineers' calendars.
Prefer email? hello@novariclabs.com