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AI Build Phase

Your enterprise AI strategy built for production.
FOUNDATION BUILDING

Unify fragmented enterprise sources into modern, trusted, context-rich foundation.
INTELLIGENCE ARCHITECTED

Create the intelligence architecture that turns data into understanding.
OPERATIONAL GOVERNANCE

Establish controls, security, and oversight so intelligence can run safely at scale.
EMBEDDED INTO WORK

Put AI inside real workflows so intelligence shows up where decisions are made.
AGENTIC ROLES

Introduce role-based agents that monitor, coordinate, and assist within defined boundaries.
DELIVERY AT SCALE

Deploy systems that are secure, observable, and built to operate at enterprise scale.

From AI Strategy to AI Capability

The AI Build Phase is where AI strategy becomes operational capability – establishing the data foundation, intelligence architecture, workflow integration, and production systems required to embed AI within the enterprise.

Enterprises today face a growing gap between AI ambition and operational reality. Organizations invest heavily in pilots, prototypes, and isolated AI tools, yet struggle to translate these early experiments into reliable enterprise capability.

Laptop AI Code Transforms Server Rack
Four structural issues typically prevent AI implementations from scaling:
FRAGMENTED ENTERPRISE DATA

Operational knowledge is scattered across systems and silos with no single-source of truth.
AI DEPLOYED OUTSIDE WORKFLOWS

Tools are not embedded where work occurs, adding complexity and limiting productivity.
OPERATING MODEL MISALIGNMENT

Roles and governance remain unchanged – increasing risk and decreasing adoption.
PROTOTYPE-TO-PRODUCTION FAILURE

Systems fail under real enterprise conditions, lacking scaleability and top-tier reliability.

Real transformational AI in the enterprise requires three connected capabilities
– built in sequence and designed to work in tandem:

1
Enterprise Data Foundation

A modern, governed data foundation that exposes the operational signals systems and teams need to innovate and compete.
2
Enterprise Intelligence Layer

Knowledge structures that create meaning – semantic models, contextual retrieval, domain relationships, and decision context.
3
Workflow‑Embedded Intelligence

AI capabilities integrated into the systems where decisions are made – so intelligence becomes part of how work gets done.
Solution Offer

AI Build Phase Scope of Work

The Build Phase translates your AI strategy into a sequenced delivery plan – focused on data, intelligence, and workflow capabilities – integrated safely at enterprise scale.

Data Platform and Integration
Create a governed signal layer by integrating the data that drives your operations.
  • Define priority operational signals and source systems
  • Build ingestion and integration patterns aligned to your architecture
  • Establish governance, access controls, and operational reliability
Intelligence Layer Architecture
Design the semantic and retrieval structures that turn signals into usable context.
  • Define semantic structure, domain concepts, and retrieval strategy
  • Implement contextual intelligence patterns that fit your systems
  • Create reusable knowledge components to support future initiatives
Workflow‑Embedded AI
Integrate AI into the moments where teams decide, execute, and learn.
  • Identify workflow leverage points and integration surfaces
  • Build AI‑enabled experiences inside the systems where work occurs
  • Implement observability and feedback loops to improve performance
Agentic Capabilities
Introduce role-based agents with clear boundaries, responsibilities, and guardrails.
  • Define agent roles, boundaries, and responsibilities
  • Implement role‑based agents tied to specific workflows
  • Establish guardrails for safe and reliable operation
Production Readiness
Harden the build so it can operate securely and reliably at enterprise scale.
  • Security controls, monitoring, and performance optimization
  • Deployment patterns aligned to enterprise operations
  • Documentation and enablement for your teams

Let's Build Your AI Foundation

Book a complimentary discovery call to align on scope and start building workflow-embedded AI with production-grade foundations.

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AI Insights

Building with AI

Explore DevIQ’s latest thinking on enterprise AI – from agentic systems and AI-augmented engineering to the practical realities of building governed, production-ready AI solutions – insights that shape the frameworks and decision models behind our AI, data, and modernization solutions.

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The AI Model is Swallowing the Agent

"Most AI efforts stall in experimentation. DevIQ helps you move past that by building intelligent agents on your data, integrating with your systems, and actually driving real work inside your platform."

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Shawn DavisonCTO and Co-Founder, DevIQ

AI Platform Partners

DevIQ partners with leading AI and data platforms – OpenAI, Anthropic, Google, Databricks, Azure, and AWS – to architect and implement solutions aligned with your enterprise environment. Our objective approach is grounded in deep experience across cloud, data, and AI ecosystems, evaluating models, infrastructure, and integration patterns to ensure systems are built for production.

FAQ

AI Build Phase Questions

The DevIQ AI Build Phase is the execution step that turns AI strategy into production-grade capability. We focus on building the data foundation, intelligence layer, and workflow-embedded systems required to operate AI safely and reliably at enterprise scale. More questions? Ask Us →

How is the AI Build Phase different from “AI implementation” services?

Strong foundation. The Build Phase is an architecture-driven execution program focused on operational capability – data foundation, intelligence layer, and workflow integration – not a one-off model deployment or isolated pilot.
Do we need to complete an AI Strategy Workshop first?

Not necessarily. Many organizations engage after completing a strategy effort (with DevIQ or internally). If strategic direction is still unclear, we can align on priorities and scope as part of the Build Phase kickoff.
Where do AI agents fit into the Build Phase?

After foundations. We design and deploy agentic capabilities role-first – tied to specific workflow leverage points – with clear boundaries, observability, and governance.
What does “production‑grade” mean in practice?

Reliable and governable. Security, governance, monitoring, performance, and operational processes required to run AI inside the enterprise – integrated with your systems and built to scale.
How do you avoid another pilot that never scales?

Workflow-first delivery. We scope around operational workflows and enterprise constraints from day one, deliver against defined outcomes, and build the foundations required for AI to operate reliably – not just demonstrate capability.
How is the engagement structured and how long does it take?

Scoped to reality. The Build Phase is delivered against mutually agreed outcomes and a timeline shaped by current state, the workflows in scope, and the depth of foundation required.
What do you need from us to start?

Access and alignment. We typically begin with stakeholder alignment, current-state architecture context, and access to key systems and signals (data sources, governance policies, and target workflows) so we can build against real constraints.
What types of workflows are a good fit for workflow-embedded AI?

High-frequency decisions. The best fits are operational workflows with repeatable decisions, clear inputs/outputs, and measurable impact (triage, approvals, service operations, risk/compliance, and internal knowledge-to-action loops).
How do you measure success during the Build Phase?

Outcomes, not demos. We define success metrics up front (cycle time, accuracy, adoption, risk reduction, and reliability) and instrument the system so performance can be monitored and improved in production.
How do you keep data secure and governance enforceable?

Controls by design. We implement role-based access, audited retrieval, policy enforcement, and observability so AI systems operate within enterprise boundaries while remaining reliable and accountable.

"DevIQ does more than just help you ‘explore AI’. We deliver a production-ready solution embedded directly into your workflows. What starts as an idea quickly becomes a measurable advantage across your product and operations."

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Eric BrownAzure Practice Director, DevIQ

Ready to Build for Production?

Schedule a complimentary discovery call to confirm fit, align stakeholders, and define the first workflow we will operationalize with enterprise-grade foundations.

LET'S BUILD