Enterprise AI agent platform
AI employees that
show their work.
Build, deploy, and govern autonomous AI agents — every action permissioned, approved, and logged. From visual workflows to multi-agent supervisors, in our cloud or yours.
an actual agent run — this is what every task leaves behind
01 · The work
Watch the work happen.
Every agent run is a legible record: what it read, what it did, who approved it. No black boxes — receipts.
02 · Use cases
Where the work piles up.
Real problems from six functions — documented by the people who live them — and the agents that clear the pile.
Resolve more, escalate less
Tier-1 Resolution
The problem
60–80% of inbound tickets are repetitive L1 work — password resets, order status, billing — burying the tickets that actually need a human.
The agent
Classifies intent, authenticates the customer, pulls order and account context, then resolves low-risk requests directly or escalates with a full reasoning summary attached.
Works with
Refund & Billing
The problem
A duplicate-charge dispute means 8–12 minutes of cross-referencing the processor, subscription record, and policy doc — on ~30% of all tickets.
The agent
Verifies identity, looks up the transaction, checks policy and fraud history, then auto-issues refunds under threshold or routes the rest to an approval queue with a full audit trail.
Works with
Escalation Signals
The problem
CSAT is a lagging indicator — by the time the survey lands or an account demands a manager, the relationship is already damaged.
The agent
Reads sentiment and attention signals across every open case in real time, generates a risk brief, and flags at-risk accounts to the CSM before they escalate.
Works with
Voice Support
The problem
61% of consumers call IVR menus a poor experience, and over 60% hang up within two minutes on hold.
The agent
Authenticates the caller, parses intent from natural speech, executes payments and shipment changes against backend systems, and hands off to a rep with a full transcript at any confidence limit.
Works with
03 · How it works
One platform, four moves.
01 · BUILD
Describe it, or draw it.
Spin up ReAct agents from a prompt, or draw workflows on a 42-node canvas — with supervisor agents coordinating multi-agent handoffs.
02 · CONNECT
Plug into everything you run.
Five model providers with fallback chains, 114 preset connectors, any REST API via OpenAPI import — plus retrieval over your documents and knowledge graph.
Models
100+ models · fallback chains · spend caps
03 · GOVERN
Policy on every action.
Guardrails check every message and tool call, approvals pause what matters, and every run seals into a hash-chained audit trail.
audit — hash-chained · WORM
15:01:08 approval.granted by=r.sudame 15:01:08 tool.executed database.insert 15:01:09 audit.sealed sha256:9c41…e2 ✓
04 · DEPLOY
Run it anywhere.
Our cloud, your VPC with Docker and Terraform, or fully on-prem. Traced end to end — tokens, cost, latency, time-to-first-token.
200ms
p50 latency
4.2M
tokens traced
$0.004
avg cost / run
04 · The platform
The platform, in numbers.
Agents
ReAct agents, workflow agents, and multi-agent supervisors with handoffs. Versioned, immutable configs with draft → publish → rollback.
Visual workflows
A DAG engine with triggers for cron, webhooks, email inboxes and events — plus a human approval node where it matters.
Knowledge
Five retrieval strategies over pgvector or Pinecone, and a bi-temporal knowledge graph on Neo4j, Memgraph, FalkorDB or Neptune.
Integrations
Native Gmail, Slack, Calendar and Drive actions; 114 preset MCP connectors; any REST API via OpenAPI import.
Models
OpenAI, Anthropic, AWS Bedrock, Azure OpenAI and DeepSeek — with fallback chains, per-provider spend caps and rate limits.
Observability
OpenTelemetry traces on every run: tokens, cost, latency, time-to-first-token. Forecasting and anomaly detection built in.
05 · The control plane
The control plane your CISO asked for.
Autonomy is only useful when you can govern it. Everything an agent does passes through policy — and leaves a sealed record.
Guardrails on every surface
11 guardrail providers — Llama Guard 3, Presidio PII, Bedrock Guardrails, OpenAI Moderation and more — enforcing on chat, tools, RAG and workflows, including mid-stream.
Humans stay in the loop
Approval nodes pause any workflow for sign-off. Agent write-backs to your knowledge graph route through a human review queue.
Permissions that mean it
Role-based access across 11 resource groups, org-scoped everything, and Postgres row-level security isolating every tenant.
An audit trail you can hand over
Hash-chained, Ed25519-signed, WORM-stored logs — exportable to Splunk, Datadog or Microsoft Sentinel in OCSF and CEF.
audit.log — live tail
14:20:52 approval.requested → finance-review 15:01:08 approval.granted by=r.sudame 15:01:08 tool.executed database.insert 15:01:09 audit.sealed sha256:9c41…e2 ✓ 15:01:09 siem.exported splunk-hec · ocsf
06 · Developers
Publish an agent as an API in one call.
Agents expose REST endpoints — or become MCP servers. Bring any tool in with an OpenAPI spec; no glue code.
# Every agent publishes as an API endpoint
curl https://api.zilionix.com/v1/agents/agt_x7k2m9p4/run \
-H "Authorization: Bearer zak_live_..." \
-d '{"input": "Summarize open P1 tickets and draft the standup note"}'07 · Pricing
Pricing you can read.
No “book a call to find out.” Every paid plan starts with a 14-day trial — no credit card.
Free
$0
For exploring — 1 agent, 100 workflow runs a month.
Pro
$49/mo
For builders — 10 agents, 2,500 workflow runs, priority execution.
Team
$149/mo
For teams — unlimited agents, 10 seats, audit logs.
Enterprise
Custom
Unlimited everything, dedicated SLA, VPC or on-prem deployment.
See it run on your work.
15 minutes. No slides. Just a live agent and its receipts.