Operationalize AI at scale.

A standard operating model for operationalizing agentic AI: business case first, governed by default, first agent in production in 8 weeks.

Book a Discovery Sprint

In 2 weeks: your prioritized use cases, a CFO-grade ROI model, and an architecture blueprint ready for sign-off.

The AI Value Gap

The hard part is no longer adopting AI. It is operationalizing it at scale.

Nearly every enterprise is already using AI. Far fewer have put it into production at scale, and the difference is rarely the technology. It is the operating model underneath.

5%

of companies are capturing AI value at scale

Around 60% see little measurable return so far, while the leaders grow revenue 1.7x faster. The gap comes down to operating model, not budget.

BCG, The Widening AI Value Gap: Build for the Future 2025 (survey of 1,250 executives)

40%+

of agentic AI projects are forecast to be canceled by 2027

The agents that last start with a clear business case and governance already in place. That is exactly where AI Factory begins.

Gartner, press release, June 2025

12%

of organizations are deploying AI agents in production today

Over half are already exploring them. The value shows up in the move from exploring to running agents in production at scale.

KPMG AI Quarterly Pulse Survey, 2025

The Nine Barriers

Nine barriers across three stakeholder layers

That gap usually comes down to nine specific barriers, spread across business, operations, and technology. Many vendors fix only the technical ones. AI Factory is built to close all nine.

Business Leadership

CFO · CEO · COO

No business case rigor

Pilots run without CFO-grade ROI models. Investment made on enthusiasm, not evidence.

Workflows automated as-is. The human-agent operating model is never defined.

No business observability

Agents run but outcomes are invisible. No KPI linkage, no audit trail to business result.

Operations & Compliance

COO · CISO · Risk · Legal

Governance void

No control plane to enforce policies. Agents act outside guardrails in critical workflows.

Workforce transition blind spot

Roles, escalation paths, override authority, and accountability boundaries are undefined.

Change & adoption failure

No enablement playbooks, no change management. The org cannot absorb what IT delivers.

Technology

CTO · Engineering · Platform

No standardized architecture

Each team builds differently. Fragmented patterns create technical debt and limit reuse.

No lifecycle standardization

No CI/CD or monitoring designed for agents. Initiatives stall before ROI is realized.

Context & knowledge disconnect

Policies and decisions never reach agent memory, which holds back compounding value.

The Operating Model

The Anblicks AI Factory Model

AI Factory answers those barriers with three decisions, taken in order: why an agent is worth building, what it should actually do, and how it runs safely in production. The business case is settled before any architecture begins.

WHY

Business Value Thesis

Every engagement starts with a CFO-grade ROI model, payback analysis, and cost-of-inaction, built before architecture begins. No agent gets designed without financial justification.

Is this the right process to automate?
What is the financial case?
What gets built first?

WHAT

Process Reimagination

Automating a process exactly as it runs today is a common and costly mistake. Every workflow is decomposed, every decision inventoried, and the human-agent operating model defined before a line of code is written.

What is the process, really?
Where do decisions live?
Who: human, system, or agent?

HOW

Agentic Execution

Standardized patterns, governed pipeline, spec-driven build, observable runtime at scale. Every agent inherits the Organization Constitution, with policies enforced at build time, never retrofitted after deployment.

Which proven pattern fits this use case?
How is compliance enforced automatically?
How does value compound post go-live?

Foundation
Contextual Intelligence,
Learning & Governance

The Engegement

8 Weeks. Four Sprints. First Agent in Production.

Those three decisions play out over four two-week sprints. Each one ends in a client-ready deliverable and a go or no-go gate, so the investment is justified before it deepens.

Weeks 1–2

✦ Discovery Complete

Discovery

Stakeholder interviews & 9-barrier assessments

Process inventory across candidate workflows

Tech landscape & data readiness review

AI Opportunity Map + initial ROI hypothesis

Discovery Report · Process Inventory · AI Opportunity Map

Weeks 3–4

✦ CFO Sign-Off on ROI

Assessment

7-dimension Value Assessment scoring

CFO-grade ROI: 3 scenarios, NPV/IRR/payback

Cost-of-inaction model per quarter of delay

5-axis prioritization + 12-month roadmap

ROI Model · Value Assessment Report · Sprint Roadmap

Weeks 5–6

✦ Architecture Approved

Recommendation

Full Build-Time + 7-layer Run-Time architecture

Agent pattern compositions per use case

Governance & human-agent operating model

Executive presentation + implementation sign-off

Architecture Blueprint · Agent Catalog · Human-Agent Model

Weeks 7–8

✦ First Agent in Production

Implementation

Factory SDK + Organization Constitution deployed

CI/CD pipeline activated, spec-driven workflow live

7-layer Runtime: Gateway, Orchestration, Memory, Guardrails, HITL, LLMOps

Reusable Asset Registry seeded for every future build

Production Agents · Factory Pipeline Live · Asset Registry

Pre-Built Advantage

The Anblicks Factory SDK, pattern library, and runtime are pre-built and battle-tested. Your engagement starts at customization, not construction. What takes others 12+ months takes Anblicks 8 weeks. Every subsequent agent on the Factory: ~2 weeks.

Why Anblicks

Six outcomes that define the difference

Not a feature checklist. These are the outcomes you can hold us to once the engagement starts.

1

You never fund an agent without knowing the ROI first

Every engagement starts with the Anblicks Business Value Thesis: a CFO-grade ROI model, payback analysis, and cost-of-inaction built before architecture begins.

2

Your agents reach production in weeks, not quarters

Because the Factory SDK, agent patterns, and pipelines are pre-built, your engagement starts with a matured foundation that avoids months of rework.

3

Compliance enforced automatically, never manually chased

The Organization Constitution is the governance layer every agent inherits at build time. Policies applied at the spec gate, never retrofitted after deployment.

4

Your agents get smarter after go-live, and value compounds

Every agent run feeds quality signals back into the Factory. Specs version. The catalogue grows. Each new build starts richer, a compounding asset rather than a depreciating project.

5

We speak your industry's language from day one

The Value Assessment Framework includes calibrated presets for Financial Services, Healthcare, and Operations, with no generic frameworks retrofitted to your context.

6

One partner. Full lifecycle. No handoff gaps.

From process decomposition to CFO ROI model to production agents to workforce transformation, Anblicks covers the complete business-to-agent-to-outcome lifecycle.

LOW COMMITMENT · HIGH SIGNAL

In 2 Weeks, Know Exactly Where to Start

The Discovery Sprint maps your top processes, identifies your highest-value use cases, and hands you a defensible business case, all before you commit to a build.

Schedule a Demo

Your Target State

What your organization looks like once the Factory is live

Once the Factory is running, this is what changes in the business, across three levels of autonomy. These are operating-model shifts, not technology milestones.

Autonomous Business Operations

Invoice exceptions resolved without human touch, zero-touch O2C
Procurement POs completed in minutes, not days
Contract redlines reviewed and risk-flagged automatically
Incidents detected, triaged, and resolved before SLA breach
Self-correcting operations at scale, 90%+ straight-through processing

Digital Twins & Augmented Workforce

Complex policy decisions with full AI reasoning and audit trail
New hires productive in days, not months, with an AI knowledge companion
Human-agent collaboration with clear escalation & override authority
Self-governing compliance baked into every agent at build time
New hire ramp time cut in half, institutional knowledge retained

Intelligent
Integration

Agent-to-agent pipelines replace brittle point-to-point integrations
Event-driven workflows triggered by real-time signals, not batch
Legacy systems accessed by agents, no API required
Cross-system orchestration with single observability layer
Legacy migration timelines cut 60%+ via Computer-Use agents

Low Commentiment · High Signal

90%+

Straight-through processing on exception workflows

60%+

Legacy migration timelines cut via Computer-Use agents

70%

Documentation time reduced in clinical reasoning

2X

New hire ramp speed with AI knowledge companion

2 Wks

Each subsequent agent built on the AI Factory

Start with Discovery

Ready to see what this means for your business?

Two weeks from now you will know which processes to automate first, what the ROI looks like across three scenarios, and what it takes to build.

Schedule a Demo

Strategy & Architecture Enablement

Digital Infrastructure

Enterprise Data Foundation

Enterprise AI & Decision Intelligence

Intelligent Experiences & Automation

Bringing AI-native mindset to rethink the industries

FinOps Studio

InventoryIQ

ADQT

CodeX Conversion Studio

DevOpsX

AI-Driven Marketing Content Creation

Pricing Optimization

Document Intelligence Agent

Decision Intelligence Agent

DataOps Support Assistant

AI-Powered DBT Transformation

Retail

Healthcare

BFSI

Commercial Real Estate

Martech, Media & Entertainment

Hospitality and Leisure

Re-imagine tomorrow as a AI-native Intelligent Enterprise

Blogs

Whitepapers

Success Stories

Presentations

The Ambition to Execution Gap in AI is Widening

Snowflake

Databricks

Google Cloud Platform

Microsoft Azure

Amazon Web Services

Sigma

Matillion

Reltio

Alation