Our development teams design and build the systems behind serious AI work: agents that carry out multi-step tasks inside your tools, knowledge built on your data, and the controls that keep it all dependable.
Your systemsCRM & sales dataDocuments & policiesEmail & tickets
Agent layer
OrchestratorPlans the steps
ResearchDraftingOperations
Knowledge layer · your data, with sources
ActionsUpdate recordsAsk for approvalSend the result
Permissions · human review · activity log
AGENTIC WORKFLOWS · KNOWLEDGE SYSTEMS · INTEGRATIONS · GUARDRAILSAN ILLUSTRATIVE SYSTEM
WHEN AN ASSISTANT IS NOT ENOUGH
Real work crosses more than one tool.
Assistants answer questions. Business processes need more: several systems, scattered knowledge, and decisions that belong to people.
01
Work that spans your systems
The task starts in an inbox, needs the CRM, touches a spreadsheet and ends in a ticket. One assistant in one channel cannot carry it through.
02
Knowledge in many places
Policies, pricing, past projects and customer history live in different tools. Useful answers need all of it, with the right access for each person.
03
Steps that need judgment
Some decisions should wait for a person. The system has to know when to act, when to ask, and how to show its work.
WHAT WE BUILD
The system behind the AI.
Every system is designed around your processes, your data and the tools your team already uses.
AGENTIC WORKFLOWS
Agents that carry the work
Agents that plan and carry out multi-step work: researching, drafting, updating records and handing off to a person when your rules say so.
Task planning and tool use
Handoffs between specialist agents
Scheduled and event-driven runs
KNOWLEDGE & RETRIEVAL
Answers from your information
Retrieval over your documents, CRM, tickets and databases, so answers come from your information and show where they came from.
Document and data ingestion
Permission-aware search
Answers with sources
INTEGRATIONS & APIS
Connected to your tools
Custom connectors to your CRM, ERP, helpdesk, email and internal databases, limited to the actions you agree on.
API and webhook integrations
Custom tools for agents
Data sync and transformation
GUARDRAILS & REVIEW
Predictable by design
Permissions, approval steps, activity logs and test sets that keep an AI system predictable and easy to check.
Human approval where it matters
Role-based access
Audit trails and evaluation tests
DEPLOYMENT & MONITORING
Running, and visible
Hosting, monitoring and usage reporting, so your team can see what the system does and what it costs to run.
Environment setup and releases
Monitoring and alerts
Usage and cost reporting
INTERNAL AI TOOLS
Built for your team
Internal apps around the AI: copilots for your staff, review queues and admin dashboards shaped around your processes.
Team copilots
Review and approval queues
Admin dashboards
THE TEAMS BEHIND IT
Developers who build with AI every day.
Our development teams design, build and maintain AI systems as their everyday work, from the first architecture sketch to monitoring in production.
They built Nexvato OS, our own AI-powered business platform, with an assistant for business owners, customer-facing agents for chat and voice, and background bots that prepare drafts for review. The same teams and the same standards build your system.
The people who design your system build it, connect it and support it after launch.
The right model for each task
We choose the models and services that fit the work, the data and the running cost.
Built to be checked
Test sets, activity logs and review steps are part of the build from the start.
HOW A PROJECT RUNS
From a mapped process to a running system.
You see the plan, the prototype and the running costs before the full build begins.
01
Map the work
We walk through the process, the systems and the data involved, and agree what a successful result looks like.
02
Design the system
Agents, data flows, permissions, review points and running costs, set out in a plan your team can question.
03
Prove it on real examples
A working slice of the system, tested against real cases from your business before the full build.
04
Build and connect
The production build, integrations, monitoring and documentation, with review points along the way.
05
Launch and improve
A staged rollout, training for your team, and ongoing support as the work and the models change.
EXAMPLES OF WHAT WE CAN BUILD
Systems shaped around real work.
Illustrative examples, not client projects. Every build starts from your own process.
An operations inbox agent
Reads incoming requests, looks up the account, drafts a reply or a ticket, and routes anything unusual to the right person.
RequestAccount lookupDraftApproval
A sales research agent
Enriches new leads from your CRM and public sources, scores the fit, and drafts outreach for a salesperson to review.
New leadResearchFit scoreDraft outreach
A document processing pipeline
Pulls the details out of invoices, forms or contracts, checks them against your rules, and writes them into your systems.
DocumentExtractValidateUpdate records
An internal knowledge copilot
Answers your team’s questions from policies, past projects and customer history, with sources and access by role.
QuestionPermission checkRetrievalAnswer + sources
BEFORE WE BUILD
Questions about custom AI systems.
Scope, data, integrations and running costs.
What is an agentic AI system?
An AI system that can plan and carry out a sequence of steps toward a goal, using the tools you allow: searching your information, updating records or drafting messages, rather than answering one question at a time. We design where it acts on its own and where a person reviews its work.
How is this different from an AI assistant or chatbot?
An assistant usually answers questions in one channel. A custom AI system connects several of your tools, draws on your business knowledge, runs multi-step work, and includes the permissions, review steps and monitoring a real business process needs.
Can you work with the software we already use?
Usually. We review your systems, APIs and data access first. Where a direct connection is not available, we can often build a custom integration or a small service in between. We confirm what is possible during discovery, before the build.
How do you handle our data and access?
Before we build, we agree which data the system can use, who can see what, and which actions need approval. Each part of the system gets only the access it needs, and its activity is logged so your team can review it.
How long does a project take?
It depends on the scope and the systems involved. We start with a mapped plan and a working slice of the system, then agree the full build and timeline from what we learn.
What does it cost to run?
Build cost depends on scope and integrations, and you get a written proposal after discovery. Running costs, such as AI model usage and hosting, are estimated in the plan and reported once the system is live.