AI Agents
Built by 10XAI agents that handle the routine judgment calls — triaging, drafting, checking, routing — inside guardrails you define.
Designed, engineered and documented by the 10X team. You own the outcome; we own the build.
The problem
Your team spends hours every day on decisions that follow a pattern — triaging enquiries, checking orders against rules, chasing missing information, drafting the same replies. The knowledge to do it well sits with two or three people, so when they are busy or away, quality slips and things fall through.
Is this the right fit?
Being honest about fit saves both sides time. This tends to work when the situation looks like the left column — and not yet when it looks like the right.
You are probably ready if
- A repeatable, rule-based decision or task consumes real hours every week
- The rules can be written down, even if they currently live in someone’s head
- Someone can own the agent’s guardrails and review its edge cases
- You want the agent to prepare or recommend, with a person approving anything commercial
Probably not yet if
- The underlying process is undefined or changes every week — fix the process first
- You want the agent to make final commercial decisions with no human in the loop
- The only goal is to “have AI” rather than remove a specific, measured cost
What 10X builds
Concrete system outputs. Not every project includes every item — scope is set to the problem, not a feature list.
How delivery works
The full 10X Operating Model →This capability draws most on these stages of the Operating Model. Each stage ends with evidence and a decision gate before the next begins.
- 01 · Review
Find where an agent genuinely earns its place — and where it would just be theatre.
- 02 · Pilot
Prove one agent against real or representative data, with guardrails in place.
- 03 · Build
Ship the agent with escalation, logging and monitoring, deployed to your environment.
- 04 · Operate and Improve
Measure against agreed criteria and tune guardrails as edge cases appear.
What’s included
- Agent scoping against a real workflow
- Guardrail and escalation design
- Integration with your existing tools
- Monitoring and failure handling
Problems this solves
- Staff spend hours on decisions a well-briefed agent could make
- Inbox and ticket triage eats the morning
- Repetitive checks get skipped when people are busy
Common questions
How do we keep control of what the agent does?
Every agent is scoped to a defined task with explicit guardrails, and anything carrying commercial risk stops at a human approval point. The agent prepares or recommends; a person decides.
What happens when the agent hits something it has not seen?
Edge cases escalate to a named owner rather than being guessed at. Escalation rules are part of the design, not an afterthought.
Which AI models do you use?
Whichever fits the task, cost and data-sensitivity constraints — model choice is made with you, and the logic is documented so you are not locked to one provider.
Is our data used to train someone else’s model?
Sensitive data classes are excluded from AI processing unless expressly agreed in writing, and delivery uses providers under data-handling terms we can show you. See our data-handling principles.
How do we know it is actually working?
Agents are measured against the criteria agreed before build — not a vanity “tasks automated” count. If it is not clearing the bar, that is a pilot result, not a sunk cost.
Related case
Regional AI Automation
Reduced manual coordination, created a single order queue, and removed dependence on individual inboxes.
Confidentiality
Agent access is scoped to the systems it needs to triage or draft in, logged where the platform allows, and revocable at any time. Sensitive data classes are excluded from AI processing unless expressly agreed in writing.
What you own
Agent logic, prompts, guardrails and configuration are documented and handed over — you are not locked into a specific vendor or model.
Often combined with
Workflow Automation
Automations that move data and trigger actions between your tools — no more copy-paste as a job description.
Internal Systems
Internal tools — portals, approval flows, registries, trackers — designed so your team actually uses them.
AI Operations
AI embedded into daily operations with governance — model choice, guardrails, human checkpoints and cost control.
Where to next
Online enquiries are being configured, so there is no form to submit yet. In the meantime, these show exactly how ai agents would be scoped, proven and delivered.