Enterprise AI operations layer
Your AI ecosystem,
governed and production-ready
elsai works within your existing Azure, AWS, Google Cloud, or on-premise environment - adding the governance, observability, and agent control your teams need to move from pilot to production without rebuilding anything.
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https://www.elsai.ai/foundry
Live
Overview
Agents
24
Observability
Guardrails
Prompts
Audit log
Integrations
Production agents
Last 24 hours · 18,420 actions
24h
7d
30d
99.94%
Policy adherence
412ms
Median latency
$0.041
Cost / action
0
Open violations
Agent actions / hour
production
Trusted by enterprises worldwide
Most enterprises don't have an AI problem. They have an execution problem.
Today, 38% of enterprises are piloting AI agents, yet only 11% have ever reached production. The bottleneck isn't the model. It's the missing infrastructure: governance frameworks that break under compliance pressure, observability blind spots that obscure cost and risk, and deployments too fragile to scale.
Most enterprises still manage agentic workflows the way they managed RPA - task by task, system by system, exception by exception.
38%
of enterprises are piloting AI agents
11%
have ever reached production
THE GAP
Several point execution loss between pilot and production
The gap is not a model problem. It is an operations problem.
Governance breaks under pressure
Policy frameworks built for demos don't hold up when compliance, audit, and risk teams get involved.
No visibility once agents go live
Once deployed, most teams have no reliable way to track what agents are deciding, spending, or missing.
Pilots don't survive contact with production
Without the right operational layer, agentic deployments stall - too fragile, too opaque, too hard to scale.
Your cloud vendor gave you AI infrastructure.
We give you the confidence to run it in production.
Enterprises that reach deployment still hit the same wall - not a technology gap, but an operations gap. elsai closes it without touching what your teams have already built.
The Execution Gap
These are not model problems. They are not cloud problems. They are the predictable gap between AI infrastructure and AI operations.
Pilots running
38%
Reach production
11%
Execution gap
27 pts
Agentic workflows
Intake · analysis · action
Operations layer
Governance · Observability · Control
Azure
AWS
GCP
On-prem
elsai fills it
elsai works alongside Azure AI Foundry, AWS Bedrock, Google Vertex, and on-premise environments - adding the governance, observability, and runtime control regulated enterprises need before any agent workflow can be trusted in production.
Governance
Observability
Prompt control
Runtime guardrails
Nothing is ripped out.
Nothing is migrated.
Your teams keep working in the environment they know.
01
Full observability with ARMS
Every token, decision, and cost tracked in real time. Defensible audit trails from day one giving CIOs and COOs clear accountability and control over every agent action.
02
Policy-as-code controls
Governance-first architecture. PII redaction and guardrails built into the core - not added after deployment.
policy.yaml
guardrail: pii_redaction
enabled: true
fields: [ssn, dob]
limits:
max_cost: $0.05
Enforced
03
Prompt and behavior control
Evolve agent logic centrally and safely. Versioning, prompt testing, and simulation built in so nothing reaches production untested.
v1.4
production
v1.3
shadow
v1.2
tested
v1.1
archived
04
LLM and cloud agnostic
AWS, Azure, GCP, or on-premises. 100+ LLMs supported. No lock-in to any model or vendor.
Azure
AWS
GCP
On-prem
We go beyond proof of concepts. We deploy AI in production and provide the governance to support it.
From your existing systems to
governed, intelligent operations.
Define the workflow and guardrails.
Choose the process, map the stages (intake, analysis, decision, action), and capture the unbreakable regulatory and policy constraints.
1
2
Design agent roles and responsibilities.
Split the workflow into specialized agents' intake, enrichment, analysis, decision, action, and follow-up with explicit human-in-the-loop points where necessary.
Connect to systems, data, and tools.
Wire agents to LLMs, RAG knowledge bases, OCR, and enterprise APIs so they can read documents, query records, and trigger downstream updates autonomously
3
4
Embed safety and behavior controls.
Establish guidelines for inputs and outputs, and create prompts/templates that outline business rules, escalation paths, and tone for agents.
Simulate, observe, and refine
Run the workflow in a controlled environment, check traces and metrics, and refine prompts and thresholds until you achieve your accuracy and risk goals.
5
6
Deploy, monitor, and scale
Promote the workflow to production with versioned configs and observability, then reuse this pattern for adjacent workflows on the same platform.
Deploying agents is no longer the hard part. Running them responsibly, inside the systems your enterprise already trusts - that is what elsai is built for.
Govern AI, right where you already stack
Enterprises have already chosen their cloud, infrastructure, and core AI tools. elsai enhances these choices with integrated observability, prompt control, and runtime guardrails - precisely within your teams' existing environments.
Azure
Azure & Microsoft
AWS
AWS-native AI
Google Cloud
Google cloud AI
On-premise
On-prem & regulated
Azure compatibility
Azure and Microsoft ecosystems
Use elsai alongside Azure AI Foundry and the broader Microsoft stack to add deeper observability, prompt governance, and runtime guardrails across agentic workflows
Explore Azure-based workflows →
Agent workflows
Your products
Intake
Analysis
Decision
Action
elsai
Operations layer
Observability
Guardrails
Prompt
Audit
Azure
Your stack
Azure AI Foundry
Azure OpenAI
Cosmos DB
Embed AI agents into your existing systems
Seamlessly integrate AI agents into your current platforms to elevate capabilities, optimize workflows, and accelerate innovation.
Beyond agents.
Intelligent orchestration of humans and AI.
The next competitive advantage is not more agents. It is agents and people working in tandem - with a live intelligence layer running across every enterprise process.
Agents alone do not run enterprises. People do - alongside agents, within systems, making decisions that require judgment, authority, and context that no model carries by default.
Process intelligence
Calculates turn-around time, cycle time, and cost-per-transaction - continuously, across every workflow.
24/7
Continuous measurement
Deviation detection
Surfaces SLA deviations and bottlenecks before they reach an audit - not as a report, as a live alert.
Live
Alerts not reports
Actionable recommendations
Not a dashboard. Not a report. A recommendation that operations teams can act on immediately.
1-click
Ready-to-act
elsai is evolving toward a human-agent workflow orchestrator that operates as a live intelligence layer across enterprise processes.
elsai foundry - where enterprise agents are made.
Where GenAI stops being a project and starts being infrastructure.
Stop managing AI like RPA. Start scaling responsibly. elsai governs Enterprise AI agents at scale. ARMS tracks every action. HIPAA/GDPR-ready. Deploy production workflows in weeks for healthcare & BFSI.
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elsai
Enterprise AI governance platform for agentic workflows. Transform your operations with confidence.