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Services

Data and AI services built for real business impact

Every DataKeys engagement fits one of three objectives: understand where you stand, build what AI requires, or scale what's working. Ten services. Three clear outcomes.

Assess

Know where you stand before you invest

Understand your AI readiness, data quality, workflow friction, and risk exposure before committing budget to platforms or agents.

  • AI Readiness X-Ray
  • Shadow AI Risk Scan
  • AI opportunity backlog
Build

Construct the foundation AI depends on

Build trusted data layers, semantic models, AI agents, workflow automations, and knowledge architectures that make AI reliable and adoptable.

  • Data foundation
  • Semantic layer
  • AI agents & copilots
  • Workflow automation
Scale

Govern, measure, and grow AI responsibly

Establish the governance, operating model, value tracking, and financial discipline required to scale AI safely and profitably.

  • AI governance framework
  • AI Center of Excellence
  • Value realization
  • AI FinOps

Assess

Know where you stand before you invest

01

AI Readiness & Strategy

Before investing in AI platforms, agents, copilots, or automation tools, organizations need to understand where they stand. DataKeys evaluates your current systems, data maturity, business workflows, reporting landscape, governance model, talent readiness, and AI opportunities.

We help you answer the questions executives are already asking: Where can AI create measurable value? Which workflows should we automate first? Is our data ready for AI? What risks do we need to control? What should we build, buy, or avoid? What should we do in the next 90 days?

Deliverables

  • AI maturity assessment
  • Data and workflow readiness scorecard
  • AI opportunity backlog
  • Use case prioritization matrix
  • Business value and feasibility scoring
  • Risk and governance gap analysis
  • 90-day AI execution roadmap
  • Executive AI strategy presentation

Best for

Organizations that know AI matters but do not yet have a clear, practical roadmap.

09

Data Trust Command Center

Data teams are spending too much time reconciling numbers, fixing pipeline failures, and answering the same question: “Which number is right?”

DataKeys helps organizations create a data quality and observability layer for business-critical data.

Deliverables

  • Critical data element inventory
  • Data quality rule library
  • Pipeline health dashboard
  • Data issue workflow
  • Data owner assignment
  • Executive trust score
  • Data quality council model
  • Data SLA monitoring
  • Remediation roadmap

Build

Construct the foundation AI depends on

03

AI-Ready Data Foundation

AI cannot scale on untrusted data. If your company has conflicting reports, inconsistent metrics, duplicate customer records, poor master data, unclear ownership, and siloed systems, AI will only amplify the problem.

DataKeys helps organizations build the governed data foundation required for reliable analytics, automation, and AI.

Deliverables

  • Data architecture assessment
  • Source system mapping
  • Data integration roadmap
  • Common data model design
  • Master data strategy
  • Data quality rules and ownership model
  • Trusted KPI layer
  • Lakehouse or warehouse design
  • Single-source-of-truth roadmap

Best for

Organizations with fragmented systems, inconsistent reporting, poor data quality, and no trusted enterprise data layer.

04

Semantic & Knowledge Layer for AI Agents

AI agents need more than access to data. They need business meaning. They need to understand approved definitions, source systems, data relationships, calculation logic, access rules, policies, process context, and which answers are trusted.

DataKeys builds the semantic and knowledge layer that allows AI agents to safely answer questions, retrieve information, and support business workflows.

Deliverables

  • Business glossary and KPI dictionary
  • Semantic model design
  • Data product catalog
  • Trusted source mapping
  • Knowledge graph strategy
  • RAG and vector database architecture
  • Metadata and lineage approach
  • Agent access-control patterns
  • Human-in-the-loop approval design

Questions this solves

Which revenue definition is official?What is the trusted source for customer data?What does “active contract” mean?Which documents are current?What actions require human approval?Which source should an AI agent trust?

05

AI Platforms, Agents & Copilots

DataKeys designs and builds practical AI solutions that connect to enterprise knowledge, workflows, and decision points.

We do not build novelty bots. We build AI systems tied to trusted data, real workflows, and measurable outcomes — secure by design, with governed access, approved knowledge sources, human-in-the-loop controls, and value tracking from day one.

Deliverables

  • Executive intelligence copilots
  • HR and policy assistants
  • Sales enablement agents
  • Customer service agents
  • Operations copilots
  • Contract intelligence agents
  • Data Q&A assistants
  • Document automation agents
  • RAG-based enterprise knowledge platforms

02

Workflow Intelligence & AI Automation

Many organizations try to automate broken processes without understanding how work actually gets done. DataKeys maps workflows, identifies friction, and designs AI automation opportunities that improve productivity, cycle time, consistency, and visibility.

We focus on workflows where teams are buried in manual work, repetitive decisions, document handling, handoffs, approvals, emails, spreadsheet tracking, and disconnected systems.

Deliverables

  • Workflow discovery workshops
  • Process pain-point analysis
  • Automation opportunity map
  • AI assistant and copilot recommendations
  • Manual effort reduction estimates
  • Business case and ROI model
  • Automation roadmap
  • Pilot design and implementation plan

Example use cases

Customer service automationSales follow-up automationContract review and summarizationFinance close supportHR knowledge assistantsField operations copilotsSupply chain exception managementDocument intake and classification

Scale

Govern, measure, and grow AI responsibly

06

AI Governance & Responsible AI

AI needs guardrails before it scales. DataKeys helps organizations establish practical governance that protects the business without slowing innovation.

We help define policies, risk controls, ownership, monitoring, approval workflows, and responsible AI practices.

Deliverables

  • AI governance framework
  • Responsible AI policy
  • Use case intake and risk classification
  • Human-in-the-loop controls
  • Model and agent monitoring standards
  • Data privacy and access controls
  • Vendor and model evaluation checklist
  • AI risk register
  • Executive governance committee design

Best for

Organizations concerned about shadow AI, data leakage, regulatory risk, inconsistent AI outputs, agent autonomy, and lack of AI ownership.

07

AI Center of Excellence Setup

A successful AI Center of Excellence is not a committee. It is an operating model.

DataKeys helps organizations establish an AI CoE that identifies use cases, prioritizes value, governs risk, creates reusable patterns, supports delivery, drives adoption, and tracks measurable outcomes.

Deliverables

  • AI CoE charter, roles, and responsibilities
  • Intake and prioritization model
  • Use case scoring framework
  • Delivery playbook
  • Governance workflow
  • Value tracking model
  • Training and adoption plan
  • AI champion network
  • Executive reporting dashboard

08

AI Value Realization Office

Many companies are investing in AI without a clear way to measure value.

DataKeys helps organizations build the discipline to track AI adoption, business impact, productivity gains, cost savings, risk reduction, and ROI.

Deliverables

  • AI initiative inventory
  • ROI baseline by use case
  • Adoption metrics
  • Productivity measurement model
  • Cost-to-serve analysis
  • Revenue and margin impact model
  • AI portfolio dashboard
  • Executive value scorecard
  • Monthly AI value review process

10

AI FinOps & Cost Control

AI cost can quickly become unpredictable. Token usage, model selection, APIs, vector storage, agent workflows, and embedded vendor AI features can create spend that is difficult to track and control.

DataKeys helps organizations understand, govern, and optimize AI spend.

Deliverables

  • AI cost baseline
  • Model usage inventory
  • Token consumption analysis
  • Cost per use case and department
  • Model routing recommendations
  • Build-versus-buy analysis
  • AI budget governance
  • ROI dashboard

Not sure where to start?

Most organizations start with an AI Readiness X-Ray — a focused assessment that shows you exactly where AI can create value and what must be fixed first.

Book an AI Readiness X-Ray