Business goal
More revenue, lower cost, faster, or less risk?
AI-native architecture and delivery partner, headquartered in Duluth, Georgia
We build the
AI-native enterprise
for 2026-2030
CES Connex designs and delivers data, AI agents and automation as one system for the 2026-2030 enterprise.
About CES Connex
AI-native architecture and delivery partner for the enterprise
1WHO
Who we are
CES Connex is a technology company based in Duluth, Georgia, designing and delivering AI-native systems for enterprises and partners across the United States.
2WHAT
What we build
Data platforms, AI agents and automation designed as one system, with governance and human control points built in.
3HOW
How we work
Every engagement starts from the owner's business question, builds the system block by block, and delivers through a 4-phase scheme.
The 5-layer architecture we deliver
WHY · A question clients often ask
Why does AI look great in a pilot and fail in operations?
Because AI needs a foundation, not a bolted-on feature. Gartner predicts over 40% of agentic AI projects will be cancelled by 2027 due to rising cost, unclear value and inadequate risk control.
Source: Gartner, 25 Jun 2025WHAT · 01/06
Foundation: infrastructure and security
Cloud servers, a gateway to AI models, permissions for who can do what, and cost control. This layer decides whether the system runs stably and securely.
WHAT · 02/06
Data: one source of truth
Figures from ERP, CRM and documents gathered in one place, cleaned, with one definition each. People and AI read the same number.
WHAT · 03/06
Knowledge: AI that understands your business
Internal policies, contracts, price lists and customer history indexed so AI answers with sources, not guesses.
WHAT · 04/06
Agents: AI takes the work and does it
An orchestrator assigns work to specialist agents for sales, operations and finance. Agents use tools and pause for approval when needed.
WHAT · 05/06
Experience: where people work
Staff and customers use it through web, mobile, a copilot inside existing software or voice. No new tools to learn.
WHAT · 06/06
Governance: 3 mechanisms around it all
Quality evaluation, a log of every step, safety guardrails. No layer runs without these three.
HOW · CES Connex works with you
We audit the 5 layers with you
- How many systems hold your data, and who owns each?
- Can internal knowledge (processes, prices, contracts) be looked up?
- Who is accountable when AI gets it wrong?
DeliverableA 5-layer map of what you have and what is missing
We put AI inside the flow of work
WHY · A question clients often ask
We gave staff ChatGPT and Copilot. Why has company productivity not moved?
AI outside the process only makes individuals faster. AI inside the process changes how the company runs. 89% of organizations use AI regularly, yet only 6% report significant profit impact.
Source: McKinsey State of AI, 25 Aug 2026WHAT · 01/03
The old way: AI on the outside
Software, a database, month-end reports, then a chatbot to ask. Whoever wants to, asks. AI does nothing on its own.
WHAT · 02/03
Reverse it: data as the foundation
Data leads the chain, knowledge sits on top, agents take work from there. This order decides whether AI can do the job.
WHAT · 03/03
The new way: AI inside the flow
Agents do the repetitive part; people approve the important points. Every AI feature ships with quality, cost and audit metrics.
HOW · CES Connex works with you
We pick the first process with you
- Repeats daily and consumes many people
- Has recorded data: orders, emails, case files
- Mistakes are recoverable, no major risk
Deliverable1 pilot process, marked where AI acts and where people approve
The AI agents we build
WHY · A question clients often ask
If I hand work to AI, who is accountable when it goes wrong?
An agent is like a new employee: a job description, a scope of authority, a work log and points where it must ask a manager. Designed right, accountability is always clear.
Source: Anthropic, Building effective agentsWHAT · 01/04
One augmented AI
A language model plus 3 things: document retrieval, tools and memory. This is the smallest unit of every agent.
WHAT · 02/04
Works in a loop with checkpoints
Receive a request, plan, use tools, check real results, pause for human review. Repeat until done.
WHAT · 03/04
Many agents work as a team
An orchestrator splits work across sales, operations and finance agents, merges results and escalates to an approver when needed.
WHAT · 04/04
3 control principles
Role-based permissions. Large transactions require a human. Every step is logged: what, why and at what cost.
HOW · CES Connex works with you
We write the agent's job description
- What it may do alone and what it must ask
- Which data it may read, which tools it may use
- Who approves, and at which step
DeliverableA one-page job description for your first agent
We match every process to the right automation level
WHY · A question clients often ask
Do I need an agent for everything?
No. Repetitive work with standard inputs only needs rule-based automation. Agents are for work that needs judgment. Gartner separates assistants, automation and agents precisely to avoid using the wrong level.
Source: Gartner, 25 Jun 2025WHAT · 01/04
Level 1: rule-based
If-then, no AI. Data entry, forwarding, reminders. Cheap, reliable, easy to audit.
WHAT · 02/04
Level 2: assistant
Q&A, summaries, drafting. AI suggests, people decide.
WHAT · 03/04
Level 3: process automation
AI completes a standard process; people handle only exceptions. Case handling, reconciliation, dispatch.
WHAT · 04/04
Level 4: decision-making agent
Agents plan and act within granted scope. Gartner forecasts 15% of day-to-day work decisions made by agents by 2028.
HOW · CES Connex works with you
We sort your processes into levels
- Are inputs standard? Yes: level 1 or 3
- Is judgment needed? Yes: level 2 or 4
- How costly is a mistake? High: add approval points
DeliverableA list of processes with automation level 1-4
The data platform we make AI-ready
WHY · A question clients often ask
Our figures live in 5 different systems. Which one does AI read?
AI is only as trustworthy as the data it reads. Revenue must be one number in every report and every agent. That is why data passes through 3 tiers before AI uses it.
Source: Databricks, medallion architectureWHAT · 01/04
Collect as-is
ERP, CRM, sensors, documents and conversations gathered and kept unchanged as the original for reconciliation.
WHAT · 02/04
Clean and validate
Deduplicate, normalize, quality-check. Documents and emails indexed so they can be found.
WHAT · 03/04
Model for the business
One definition per metric. Revenue means revenue in every report and every agent.
WHAT · 04/04
Put to use
Agents, assistants, dashboards and other software all read from one standard tier. Quality measured daily.
HOW · CES Connex works with you
We take the data inventory with you
- List sources: which system, who owns it, how it updates
- Pick 10 core metrics and agree on definitions
- Identify data still missing for the pilot process
DeliverableA data inventory and 10 standard metrics
Roadmap
The 2026-2030 roadmap we walk with you
Which year is still early enough to start?Global AI spending is forecast at $2.59 trillion in 2026, up 47%. A company that starts standardizing data in 2026 has two years before agentic AI becomes the default in 2028.Source: Gartner, 19 May 2026 and 25 Jun 2025
40%
Gartner forecast · Now
2026
Task-specific agents in applications
Gartner forecasts 40 percent of enterprise apps will feature task-specific agents, up from under 5 percent in 2025.
>40%
Gartner forecast
2027
Prove value, cut projects without ROI
Gartner predicts over 40 percent of agentic AI projects will be cancelled over unclear cost and value. This stage decides who continues.
33%
Gartner forecast
2028
Agentic AI becomes the default
33 percent of enterprise software includes agentic AI; 15 percent of day-to-day work decisions are made autonomously.
AI-native
CES Connex direction
2030
The AI-native enterprise
CES Connex direction: most standard processes run automatically under control; people focus on decisions and relationships.
Source: Gartner press releases, 26 Aug 2025 (40 percent of apps with agents in 2026) and 25 Jun 2025 (2027 cancellations, 33 percent and 15 percent in 2028). The 2030 stage is CES Connex direction, not a Gartner forecast.
What we hand over: one map, not six pieces
WHY · A question clients often ask
When it all comes together, what does my business look like?
One system: data flows in, agents do the work, people approve, governance wraps around it. Not six separate projects, not six vendors.
Source: CES ConnexWHAT · 01/03
The 5-layer frame
Infrastructure, data, knowledge, agents, experience. The frame of every system CES Connex delivers.
WHAT · 02/03
Data flows in
From raw sources through 3 tiers into the data platform, then up to the knowledge layer for agents.
WHAT · 03/03
Agents work, people approve
Agents draw on knowledge, use tools, deliver results to where people work. People approve key points. The loop closes.
HOW · CES Connex works with you
We place your business on the map
- Color the blocks you have and the ones you lack
- Trace the pilot process through the blocks
- Fit the process into the 4-phase implementation scheme
DeliverableA 12-24 month target map
How CES Connex delivers
From a business question to a running system
CES Connex works with the owner on a 6-cell canvas and delivers through a 4-phase scheme, with a decision gate between each phase.
The 6-cell canvas we complete with clients
01See section 02
02See section 02
Priority process
Repetitive, people-heavy, with recorded data
03See section 04
Automation level
Level 1-4 by the judgment required
04See section 05
Data required
Sources, owners, 10 standard metrics
05See section 03
Human control points
Who approves, at which step, above what threshold
06See section 01
Metrics
Cycle time, cost per transaction, error rate
CES Connex 4-phase implementation scheme
0
Diagnose
2-3 weeksFill in the 6-cell canvas, audit the 5 layers, choose the pilot process.
OutputCurrent-state map and proposed architecture
Decision gate: Worth doing?
1
Pilot one process
6-8 weeksStandardize data for that process, build the first agent with approval points.
OutputA live process with before-and-after figures
Decision gate: Scale it?
2
Scale by department
1-2 quartersShared data platform, more agents per department, central governance.
Output3-5 AI-native processes, an internal team running them
Decision gate: Standardize company-wide?
3
Operate AI-native
OngoingMeasure quality, cost and risk daily. Raise automation levels based on real data.
OutputOne system, one map, continuous improvement
Durations reflect CES Connex delivery experience and vary with company size and data readiness.
Solutions
5 AI-native platforms by domain
Pick a domain to see the platform and agents CES Connex delivers.
Enterprise operations
Operations platform with agents that monitor workflows, cost and data, raising alerts early instead of end-of-period reports.
IndustriesManufacturingLogisticsDistributionRetailB2B services
Agents includedInternal AI assistantAutomated reportingWorkflow alertsPerformance analyticsDemand forecasting
How we deliver
7 steps from data to agents running in production
Every step has a quality checkpoint before the next one begins.
AI-native project
Fixed scope, timeline and price.
Dedicated engineering team
An AI and data team working inside your process.
Long-term transformation partner
Alongside you on the 2026-2030 roadmap.
AI strategy and partnerships
Sets the AI-native roadmap with each client.
AI-native architect
Designs the 5 layers, model gateway and security.
Head of data platform
Lakehouse, semantic layer, data quality.
Head of agent engineering
Orchestrator, tools, evaluations.
Delivery manager
Timeline, approvals, handover and operations.
Market Data
The 2026 AI investment landscape
Figures from public reports by international research organizations. Click a card for detail.
$2.59T
Worldwide AI spending in 2026
A 47 percent increase year over year. AI services alone account for $585.5 billion and AI software for $453.2 billion.
Gartner press release, 19 May 2026Original report ↗
89%
Organizations using AI regularly in at least one business function
Based on 1,719 participants across 97 nations, surveyed 4 May to 8 June 2026.
McKinsey, The State of AI, 25 August 2026Original report ↗
44%
Organizations scaling AI across the enterprise
Up from 38 percent in 2025. The gap between large and smaller organizations stands at 54 percent versus 33 percent.
McKinsey, The State of AI, 25 August 2026Original report ↗
40%
Enterprises above $1B revenue scaling AI agents
Up from 27 percent in the previous survey. Smaller organizations remain flat at 22 percent.
McKinsey, The State of AI, 25 August 2026Original report ↗
37%
Organizations attributing EBIT impact to AI use
Essentially unchanged from 2025. Only 6 percent qualify as high performers on value captured.
McKinsey, The State of AI, 25 August 2026Original report ↗
40%
Enterprise apps featuring task-specific AI agents by 2026
A sharp rise from less than 5 percent in 2025, according to the Gartner forecast.
Gartner press release, 26 August 2025Original report ↗
These figures are industry data published by independent research organizations and are presented to describe market context. They are not CES Connex performance figures. Project references and specific service commitments are provided in the capability dossier shared directly with each partner.
Start a conversation
Start with one process
Send us the process that consumes the most people. Within 3 business days you receive a proposed architecture map, the right automation level and a resourcing estimate. That is the diagnosis phase of our implementation scheme.
- Emailcontact@cesconnex.com
- Websitecesconnex.com
- Headquarters1640 Satellite Blvd, Ste. 100, Duluth, GA 30097, USA
- Response timeWithin 3 business days