Enterprise AI · 2026
The Agentic Enterprise
The question in 2026 is no longer whether to use AI. It is whether your AI does real work — grounded in your data, governed by explicit guardrails, and accountable in production. Cloud23 engineers that reality on AWS, Anthropic and Salesforce Agentforce.
The shift
Copilots suggested. Agents do the work.
For three years enterprises ran AI pilots. The gap that remained was always the same: from a clever demo to a system that acts on real data, safely, at scale. In 2026 that gap closes — and closing it is an engineering discipline, not an experiment.
- Yesterday
- Assistants and copilots that suggested — a human still did the work.
- The trap
- Impressive demos that never survived contact with real data or audit.
- 2026
- Governed agents that take action in production — and answer for it.
The stack
One agentic stack. Three foundations.
We don’t bet the enterprise on a single vendor. We engineer the best of AWS, Anthropic and Salesforce into one accountable system — and swap any part when the problem demands it.
AWS
The cloud the agents run on
Amazon Bedrock and AgentCore for model access, agent runtime, memory and tools — secure, scalable and inside your own account.
- Bedrock
- AgentCore
- Model hosting
- Guardrails
Anthropic
The reasoning
Claude as the reasoning engine — the frontier models we use to plan, judge and act, chosen for their behaviour under real enterprise constraints.
- Claude
- Tool use
- Extended thinking
- Evaluation
Salesforce
The enterprise system of action
Agentforce and Data Cloud so agents reason over governed CRM data and take real actions inside service, sales and operations — one strong platform among many.
- Agentforce
- Data Cloud
- Flows & APIs
- Escalation
Engineered together by Cloud23 — one team accountable from use case to live operations.
From strategy to intelligent operations
Enterprise AI succeeds on discipline, not enthusiasm.
In banking and insurance — where much of our work sits — the discipline below is not optional. It is how an agent earns the right to touch a customer.
- 01
Choose the work
Candidate use cases ranked by value, feasibility, data readiness and risk — a sequenced portfolio, not a wish list.
- 02
Ground it in truth
Agents reason over data that is actually correct — grounded in CRM, Data Cloud and knowledge, with the gaps closed first.
- 03
Set the guardrails
Every agent's scope, permitted actions, and escalation rules are defined and documented before a customer meets it.
- 04
Engineer the actions
The flows and integrations — often via MuleSoft — that let agents do things, safely and within permissions, not merely answer.
- 05
Evaluate before customers do
Behaviour tested systematically against scenarios, accuracy thresholds and escalation criteria — before and after go-live.
- 06
Operate with AgentOps
Containment, escalations and cost monitored in production, with a cadence for tuning topics, grounding and guardrails.
We ship our own
We build on this in our own business — not just for clients.
Fallon, Cloud23’s AI-powered revenue lead for small and medium businesses, is built on Agentforce. Shipping our own agent means we have confronted grounding, guardrails, evaluation and cost behaviour as an owner — which changes how we advise you.
Put an agent to work — safely
Bring us a task worth automating. We'll tell you honestly whether it's ready, and if it is, engineer the agent that does it in production.