Nivalabs.ai
AI systems that fit
how your business runs
We design and ship AI agents, LLM applications, and workflow automation that connect to your tools, data, and teams. Clear scope. Reliable delivery. Systems you can operate.
Production systems
Built for live operations
Agents & LLMs
Designed around real work
Global delivery
US · EU · APAC
What we build
Production-grade AI for operations teams. We start from the workflow, not the model, and ship systems your people can use day to day.
01
AI Agent Development
Agents that read context, call tools and APIs, and complete multi-step work inside your operations. Fewer handoffs, faster cycle time.
Learn more02
Custom LLM Applications
Domain assistants, knowledge systems, and decision support built on retrieval, evaluation, and governance. Answers grounded in your data.
Learn more03
AI MVP and PoC Development
Focused pilots that prove value, data fit, and integration risk before you fund a full build. Clear go or no-go evidence.
Learn more04
AI Workflow Automation
Document flows, approvals, and operational handoffs automated with models, rules, and human review. Less manual processing.
Learn more05
AI Integrations
Connect AI to ERP, CRM, and internal platforms without replacing the systems your teams already trust. Works inside your stack.
Learn moreWho we help
We work best with organizations that have a real operational problem, access to systems and data, and an owner ready to run what we ship.
Operations and process owners
Teams drowning in documents, handoffs, and exception handling who need software that fits the way work already moves.
Product and engineering leads
Leaders who want production AI with clear architecture, evaluation, and ownership, not a demo that dies after launch.
Domain-heavy enterprises
Logistics, aviation, marine, supply chain, and similar environments where context and system of record matter more than novelty.
Not sure if you are a fit? See how engagements work or tell us about the workflow.
How engagements work
A simple structure from first conversation to a system in production. No open-ended experiments without a path to ownership.
Discover
Map the workflow, data sources, constraints, and success metrics with the people who own the work.
Design
Define architecture, tool access, evaluation criteria, and the human review points that keep risk contained.
Pilot
Ship a focused build against real data and real users. Measure outcomes before you scale spend.
Operate
Harden for production, document ownership, and hand off monitoring so your team can run the system.
NIVA · Agentic chatbots for industry teams
Personas, workflows, and white-label deploy without a long build cycle.
Built for operational domains
We design around the work that already exists: documents, systems, handoffs, and the people who own them.
Marina and ports
Berth allocation, scheduling support, vessel data handling, and day-to-day operational coordination where timing and context matter.
Explore solutionLogistics
Shipment intelligence, document automation, demand signals, and operational visibility across carriers, warehouses, and partners.
Explore solutionAviation
Planning support, knowledge retrieval, documentation automation, and decision aids for teams that cannot afford guesswork.
Explore solutionEnterprise operations
Internal assistants that surface policies, automate handoffs, and reduce repetitive work across departments.
Explore solutionSupply chain
Forecasting support, inventory signals, and clearer visibility across suppliers and fulfillment.
Explore solutionSelected scenarios we ship against
Concrete problems with measurable outcomes. If your case looks different, we still start from the workflow.
Document-heavy intake
Extract, validate, and route information from invoices, manifests, or claims into the systems operators already use. Hours of manual entry cut to minutes with review only on exceptions.
Knowledge that stays findable
Give teams grounded answers over policies, SOPs, and product docs without hunting through shared drives. Faster onboarding and fewer repeated questions to specialists.
Operational assistants
Agents that check status, update records, and escalate when judgment is required. Frontline teams spend more time on decisions, less on swivel-chair work.
Workflow automation with humans in the loop
Automate approvals and handoffs where rules and models both play a role, with clear ownership. Throughput rises without removing accountability.
ERP and CRM assisted workflows
Summaries, recommendations, and write-backs inside the platforms your teams already trust. Adoption without a parallel shadow system.
Logistics exception triage
Surface shipment context, documents, and next actions so operators clear exceptions faster. Smaller backlogs and clearer handoffs across partners.
Browse the full catalog on the use cases page.
When Nivalabs is the right partner
We are selective about scope. The goal is a system your team can operate, not a slide deck of AI possibilities.
A strong fit when
- You have a concrete workflow with measurable pain (time, errors, throughput)
- Systems of record and sample data can be made available for a pilot
- Someone owns the process after launch
- You want architecture, evaluation, and handoff, not only a prototype
Not the right fit when
- You only need a marketing demo or one-off chatbot with no data grounding
- There is no owner for the workflow or no path to production systems
- Success cannot be defined beyond 'explore AI'
- You want model research without an operational outcome
How we decide what to build
Three commitments that keep projects practical and production-ready.
01
Workflow first
We design from the job to be done: inputs, systems, handoffs, and owners. Models come after the process is clear.
02
Grounded and reviewable
Answers and actions stay tied to approved sources and tool calls. Exception paths keep people in control where it matters.
03
Built to be owned
Documentation, monitoring, and handoff are part of delivery. Your team should be able to operate what we ship.
What production-ready means here
We treat reliability, ownership, and measurable outcomes as part of the build, not a follow-up project.
Evaluation before scale
We define success criteria and test against real samples before a pilot is treated as production-ready.
Integration without rip-and-replace
Systems connect to the tools you already run. We do not force a greenfield stack to ship value.
Operator handoff
Runbooks, ownership, and monitoring so the system does not depend on a single engineer after launch.
Scoped commercial clarity
You know what is in, what is out, and what the next decision point is. No open-ended research retainers by default.
Common questions
Straight answers about how we work with operations and engineering teams.
How long does a typical engagement take?+
Discovery and a focused pilot often land in weeks. Production hardening depends on integrations and review requirements. We scope timelines against a clear outcome, not open-ended research.
Do you replace our existing systems?+
Usually no. We design AI to sit alongside ERP, CRM, and internal tools through APIs and controlled workflows so operators keep working in familiar places.
What do you need from us to start?+
A description of the workflow, who owns it, which systems and data are involved, and what success would look like in 60 to 90 days. Access for a pilot follows once scope is clear.
How do you handle risk and governance?+
We define human review points, evaluation criteria, and auditability up front. Tool access and data boundaries are part of design, not an afterthought.
More detail on the FAQ page.
Where to go next
Pick the path that matches where you are: exploring problems, evaluating delivery, or ready to talk scope.
Explore use cases
See where agents, LLM apps, and automation typically land in operations-heavy businesses.
Browse use cases →Understand delivery
From discovery through pilot and production handoff: how we structure work and ownership.
How we work →Start a conversation
Share the problem and systems involved. We will respond with clear next steps.
Contact us →
Let's build the right system
If you have an operational problem that AI might solve, we will help you scope it clearly and decide what is worth building.
From the field
Practical notes on agents, LLM applications, and automation from production work.