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ZeaIQ is the agentic automation platform for the enterprise. Design agents in a conversation, connect them to your systems, documents and people, and deploy them to every channel — with evals, policy rules, ROI and audit built into one runtime.
SOC 2 Type IIISO 27001HIPAAGDPRSaaS, dedicated or air-gapped
AI Workflow Builder
Works with the models, data and channels you already run
The platform
Agents, teams, workflows, browser robots, documents, data and app creation share one identity layer, one governance model and one run ledger — so nothing ships outside your controls.
Build
Describe an agent and the studio builds it. Compose specialists into teams with five orchestration patterns.
Automate
Durable workflows with human approval gates, plus browser agents you teach by showing.
Understand
Grounded answers, document extraction with review, and analyst-grade answers from your data.
Create
Turn a prompt into an internal app or a board-ready deck grounded in your data.
Run & govern
ROI, evals, policy rules, a kill switch — and every channel from Teams to MCP.
How it works
One platform covers the whole agent lifecycle, so the thing you tested is exactly the thing that runs — and you can prove what it did.
01 — Design
Agent Studio turns a conversation into a configured agent — instructions, model, tools, knowledge and guardrails — and tests it before anything is published.
Browser automation
Agents operate real websites in a live browser. Teach a task by demonstrating it and ZeaIQ records a recipe that replays without any model call — and hands over to the AI agent on the same page if the site changes.
Recipe · Supplier remittance
0 model callsWritten as
“Credits over $100 need approval from a supervisor.”
when tool = issue_credit and args.amount > 100 USD on chat, whatsapp, teams, api then require_approval(role="supervisor")
Held: issue_credit · $240.00
Customer Service Concierge · WhatsApp · waiting 2m
Governance
Policy rules run as middleware on every tool call — block, hold for approval or allow. Write them in plain English, review the compiled rule and dry-run it. A prompt can't talk its way past a rule.
Gating suites must pass and an approver signs off before a version goes live.
Suspend an agent and it stops on chat, API, channels, MCP, A2A and teams at once.
A per-org SHA-256 hash chain with CSV, JSON and PDF export.
Value
Agent Ops turns real production runs into hours saved, net value and ROI per agent and workflow. Try the same model on your own numbers.
Estimated value
$360k
net value per year, after AI costs
Illustrative estimate. In production, Agent Ops calculates these figures from real runs using the same baseline fields — minutes per case, hourly rate and value per case.
Open by design
Call agents and teams as OpenAI-compatible models, discover them over A2A, or let any MCP client use them as tools. Bring your own tools in with OpenAPI specs and MCP servers.
from openai import OpenAI
# Any OpenAI client works — point it at ZeaIQ.
client = OpenAI(
base_url="https://your-instance.zeaiq.ai/v1",
api_key=ZEAIQ_API_KEY, # scope: agents:openai_compat
)
reply = client.chat.completions.create(
model="agent:6d85c1fb-0dc7-4529-a793-74d7e1d7c7d4",
messages=[{"role": "user", "content": "Summarize today's payment exceptions"}],
stream=True,
)Solutions
From payments operations to citizen services, ZeaIQ runs the processes where accuracy, approvals and audit matter most.
Why ZeaIQ
Most agent programs stall stitching together point tools — each with its own identity, its own audit trail and its own bill. ZeaIQ brings the whole lifecycle into one governed runtime.
The usual stack
Deploy anywhere
Run ZeaIQ as SaaS, on a dedicated instance or fully air-gapped — and choose from nine model providers, including private and sovereign options, with call-time failover.
The fastest start. Each organization is a hard tenant boundary with its own stores, credentials and audit chain.
Your own instance in your cloud region, on Docker Compose or Azure Kubernetes Service.
Fully disconnected deployments with signed licenses verified offline and offline renewal.
Bring your own models — nine providers, one switch per agent
Security & trust
Independently audited controls, least-privilege access and complete traceability — on every surface.
SAML 2.0, OIDC, LDAP/Active Directory and Microsoft sign-in, with MFA and email codes.
Seven roles and 60+ fine-grained permissions. Data sources are deny-by-default.
Organizations are hard tenant boundaries. Secrets are encrypted at rest.
Append-only, hash-chained audit logs with export for every action.
ZeaIQ is an agentic automation platform. Teams use it to build AI agents and multi-agent teams, orchestrate them in durable workflows with people and systems, deploy them to every channel, and operate and govern them in production — all on one runtime.
Chatbot builders stop at conversation and RPA stops at clicks. ZeaIQ combines agents, workflows, browser automation, document extraction and analytics, and adds the production layer they lack: eval-gated releases, policy rules enforced outside the model, a kill switch, a run ledger and ROI.
OpenAI, Azure OpenAI, Azure AI Foundry, Anthropic, Google Gemini, AWS Bedrock, Ollama, Core42 Compass and ZeaLLM. Each organization can bring its own provider keys, choose a model per agent and configure failover to a secondary model.
Yes. ZeaIQ runs as multi-tenant SaaS, as a dedicated single-tenant instance in your cloud, or fully air-gapped on-premises with signed licenses that are verified offline.
Every release can be gated by eval suites and an approver. At runtime, policy rules check every tool call outside the model and can block it or hold it for approval. A kill switch stops an agent on every surface at once, and every action lands in a hash-chained audit log.
Set a baseline per agent or workflow — minutes per case, loaded hourly rate and direct value per case. Agent Ops applies it to real production runs to report hours saved, FTE equivalent, net value after AI cost, ROI multiple and straight-through rate.
We start with one process you choose, build it with you on your own data and systems, put it through your approval and governance flow, and set ROI baselines so the results are measured from real runs.
See ZeaIQ on your own processes. We'll map a use case, build it with you and show the governance and ROI views your stakeholders will ask for.
