An agentic platform that ships squads of purpose-built agents for software, business, industry & care — composable, memorable, mediated.
70% of enterprise AI pilots stall because they rely on a single prompt. The window to ship production-grade multi-agent systems is open — for the next 18–24 months.
LLMs answer prompts, but real workflows demand specialised roles working in parallel — not a single model doing everything.
Tools and protocols — OPC-UA, MQTT, APIs, EHR — live in silos. Hand-offs break down the moment you cross a boundary.
Context vanishes after each run. Agent squads need shared, durable memory and continuous improvement to compound value.
Closed stacks block experimentation. Teams need freedom to mix SDKs and open-source LLMs without rebuilding from scratch.
Why now: 70% of enterprise AI pilots stall at single-prompt automation. The window to ship production-grade multi-agent systems is open — for the next 18–24 months. AgenticSys is engineered to capture that window.
AgenticSys ships squads of agents — purpose-built per domain — with roles, shared memory, pluggable SDKs, native protocol mediation, and observable, replayable runs.
Every squad is composable: pick the SDK, pick the LLM, pick the protocols and the role catalogue. The platform handles memory, hand-offs, and audit. You ship the outcome.
A Spotify-model squad: five specialised agents shipping features end-to-end. Each role is designed in — not bolted on — with traceable hand-offs and review artifacts built into every sprint.
Shipped feature increment per sprint, with traceable hand-offs and review artifacts.
The first agent platform built so SMEs compete with enterprise tech — at SME prices. NexoIA acts as both seller and connector: it remembers every customer, attends leads 24/7, and stitches together channels, systems and processes into one brain that learns every day.
Lost leads · Slow credits · Disconnected systems · No live visibility. Attended from day one with a dashboard of live numbers that does the selling.
Four Smart Factory agents mediating OT protocols for a renewables platform. OPC-UA handles industrial data exchange across PLCs, SCADA and historian. MQTT provides lightweight pub/sub for control mechanisms at the edge.
Live wind & solar fleet visibility, autonomous derating, and closed-loop control without bespoke gateways.
Six agents orchestrating a complete clinical encounter with the patient at the centre. Mediates FHIR/HL7, hospital ERP, imaging PACS, lab systems and voice dictation — all natively.
Faster, safer triage · Coordinated care plans · Records auto-updated in EHR · Family communications drafted · Audit trail by default.
One orchestrator across the emerging landscape of agent-to-agent protocols. AgenticSys is the mediator: one platform, every protocol — without lock-in. As new protocols emerge, the mediator extends, not replaces.
Future-proof your agent infrastructure. Whatever protocol the ecosystem settles on, AgenticSys already speaks it.
Agents that share meaning — not just messages — via Knowledge Graphs and ontologies. OWL 2 provides reasoning over classes and properties; RDF/RDFS the universal data fabric; SPARQL graph-native lookups; SHACL validation rules. From token soup to triples.
Shared meaning across vendors · Every claim traceable to ontology classes · Cross-domain reuse for industrial, clinical & financial squads · Inference rules that catch errors LLMs miss.
Use the right tool for each job. AgenticSys abstracts away SDK lock-in so you can mix frameworks per squad, per task, per use case.
Tool calls, hand-offs, tracing
Roles, tasks, processes
Multi-agent conversation graphs
Durable, queryable, per-squad and per-customer
Replayable runs, traces, evals & audit logs
>92% pass rate on golden eval suite
Orchestration, mediation, and observability — each layer purpose-built, composable from day one.
The squad palette spans: Software (Spotify), NexoIA / SME, IIoT Smart Factory, Hospital, Protocol Mediator, Knowledge Graph / OWL — and any custom domain you plug in.
A repeatable five-step playbook that takes any domain from first conversation to production outcome in 30 days.
Map the workflow, pick the squad and protocols.
Roles, SDK, LLMs, memory, tools — composed for the domain.
End-to-end run in production — day 1 prototype that wows.
Evals, traces, outcome KPIs — every metric from day one.
Guardrails, audit, scale-out — built for production load.
Day 1: a prototype that wows. Day 30: a measurable outcome on the dashboard.
Each milestone adds a live squad and compounds platform value. Seed round funds two pilots in parallel and the squad marketplace.
Spotify-model squad in production — five roles, traceable hand-offs, shipping increment per sprint.
First SME closes, live dashboard deployed — leads attended, credits processed, hours saved.
OPC-UA + MQTT bridges in field — live wind & solar fleet visibility, autonomous derating.
FHIR / HL7 mediation live — faster triage, coordinated care plans, EHR auto-updated.
Squad templates & shared memory available — zero-CAC revenue from catalogue goes live.
Codex / Opus / Qwen / Llama running side-by-side — 55/45 open/closed LLM mix, bending the inference cost curve.
Every squad is observable. Every metric is tracked. Outcomes are on the dashboard — not in a slide.
Every risk is engineered for — not managed after the fact.
Tool-grounded agents, evals and golden test suites catch errors before they reach production.
SDK abstraction layer and open-LLM fallback mean no single vendor can hold the platform hostage.
Per-tenant memory isolation and field-level redaction keep customer data strictly separated.
Replayable protocol bridges and canary releases isolate and rollback issues before they spread.
Squad templates lower the build bar — teams ship squads without needing senior ML engineers on every project.
FHIR / EU AI Act mappings built in, audit by default — compliance is a feature, not an afterthought.
Six squads today, six more tomorrow — plug a new domain in days.
memory · evals · audit
Engineered to ship — not just to chat.