The agent gap
Great in daily life, then you open the enterprise systems at work and the AI falls apart — isolated data, no governance, no context.
EasyStack Agent Platform
Cortex Enterprise Agent Platform
One platform for the whole lifecycle — build, govern, observe, run. Turn AI capability into governed, reusable, publishable digital workers, and let the people who know the business build them safely.
Reality check
Everyone is deploying agents. Nine in ten stall
90% of agent projects stall between demo and production. Consumer AI is fluid. Enterprise AI stalls on data, governance and trust — the gap is rarely the model.
No data foundation
Data sits in spreadsheets, email, legacy ERP and scattered databases the agent cannot reach. Wiring it up takes longer than the agent itself — wrong data, wrong answers.
Misplaced expectations
Some overestimate it, expecting full automation out of the box; others dismiss it as a shell — wrong scenario, wasted investment.
Building it is an engineering problem. Applying it is a judgement problem — we solve both.
Proven in production
The economics at scale
20+
Active scenarios
Core financial scenarios at a top-tier state-owned bank.
-80%
Deployment cost
Deployment cost, cut by more than 80%.
1 day
Time to go-live
From month-level release cycles to go-live in a single day.
Reference deployment: 60%+ higher throughput on the same infrastructure.
Scenario boundaries
Where agents pay off, and where they do not
Across service, finance, HR, sales and IT the test is the same: high frequency, clear rules, contained impact.
Autonomous
High frequency, clear rules, contained impact
- Customer Q&A and ticket triage
- Knowledge Q&A, report generation
- Self-serve data queries, alert triage
Agent acts on its own
Human in the loop
Partial understanding, judgement, moderate impact
- Model review, change risk assessment
- Credit pre-screening, invoice checks
- Lead scoring, complex workflow upkeep
Human reviews and approves
Not yet · human-led
Novel, high-risk, regulated, irreversible
- Final call on major incidents
- Sensitive budgets, fund transfers
- Irreversible production changes
Human decides
Autonomous zones run on sandboxes; assisted zones on observability and approval; human-led zones on audit and private deployment.
Platform positioning
Build it, govern it, see it, keep it private
One platform for the whole lifecycle: build, govern, observe, run.
Agent Factory
Business users build their own
App Marketplace
Reusable skills and apps
Operations Hub
Observable and governed
Three structural differences
Self-developed engine
Fully self-developed — no third-party framework, fully transparent and modifiable.
Full-chain observability
Every agent, RAG and workflow step is traceable — debuggable and reviewable.
Private and secure
Full-stack intranet, data never leaves. RBAC plus human approval.
In short — turn AI capability into governed, reusable, publishable digital workers, not a scattering of chat windows.
Who uses it
Business people can now build with AI
The core question: can the people who know the business build, publish and govern AI agents themselves — and wire them safely into daily work?
Business users
Build without writing code
- Chat or drag-drop workflows, no code
- Query data, read docs, call tools, act
- Orchestrate branches, loops and approvals
Business managers
Governed and compliant
- Fine-grained rights over tools and data
- Sensitive actions trigger human approval
- Full audit trail for every change
IT and platform ops
Central control, build once deploy widely
- Manage models and integrations
- Build once, publish via secure API gateway
- Private deployment, data never leaves
Governance
Granular RBAC control, human approval on risk
RBAC everywhere
Role-based control across tools, skills and apps (user groups × roles × individuals, additive union model).
Security tiers + approval
Critical tools carry a security tier that gates them behind approval — dangerous actions stay blocked.
Sandbox isolation
Code, documents and browsers run in Docker container sandboxes with automatic lifecycle management.
Full audit trail
Every tool call, API access and data change is logged, including whether the run was sandboxed.
Private deployment
Full-stack intranet deployment — data never crosses your boundary.
Enterprise NL2SQL
Plain-language queries — safe, self-improving
Self-serve data
Plain language to SQL to execution to chart — no queueing for the data team.
Safe for production
Read-only connections, AST whitelisting and execution timeouts — data cannot be deleted.
Self-correcting
Self-healing retries; the AI never guesses identifiers from memory (anti-hallucination).
Gets sharper with use
Approved question-to-SQL pairs are stored for reuse, so repeated questions get faster.
Automatic charts
Time series to line, OHLC to candlestick, rankings to bar — swap to a pie chart instantly.
Tool ecosystem
From chatting to doing — wired into your APIs
60+ built-in tools
Files, code execution, browser, computer control, image generation — ready out of the box.
MCP protocol support
Standard MCP connects you to the external service ecosystem.
Automatic API wrapping
Any existing HTTP API can be wrapped and standardised into OpenAI-format function tools, so legacy interfaces become tools the AI can call.
Apps as tools
Knowledge bases and LLM apps are directly callable as tools, and can orchestrate each other.
Why it matters: standardised API wrapping — give the AI your existing services without rewriting the backend.
Technology foundation
Self-developed, sovereign, no vendor lock-in
Self-developed agent engine
Tool loop, context compression, sub-agent scheduling, kill/steer — all in-house.
Multi-vendor LLM abstraction
OpenAI / Claude / Qwen / DeepSeek / Azure / Ollama — switch freely, mix domestic and international models.
Native pgvector retrieval
Knowledge and memory run directly on PostgreSQL — no separate vector database.
Modern stack
NestJS + Vue3 + PostgreSQL/pgvector + Docker.
Sovereign and fully controllable — not tied to any single model vendor.
Customer value
Clear value for every stakeholder
Business units
- Answers from your documents
- Data they can query themselves
- Processes that run themselves
- Gets smarter about the business
IT & Security
- RBAC control
- Approval on critical actions
- Full-chain observability
- Private deployment, data stays in
Management
- Fully sovereign and controllable
- Not locked to a cloud vendor
- Knowledge captured as an asset
- Fast, tailored deployment
Learn more about the Cortex Enterprise Agent Platform
For scenario selection, private deployment and technical architecture, talk to our sales and support team.