We don't start with a model.
We start with an accountable workflow.
AI agents built by Cyberate Technologies, deployed first inside DDDI's own companies — on live quoting, scheduling, reporting and finance systems.
Every agent knows what it may read, what it may produce, who confirms it and where its exceptions go. That is the difference between an agent and a chatbot.
What makes an agent different.
Generic AI tools answer questions. Generic automation repeats rules. An agent carries a defined role inside a running system — and hands the decision back to a person.
| Generic AI tool | Generic automation | A DDDI agent | |
|---|---|---|---|
| Starting point | A chat box | A fixed rule | An accountable workflow |
| Understands documents | Loosely, on request | Barely | Drawings, specs, contracts — parsed with confidence flags |
| When context changes | User re-prompts | It breaks | The agent flags the exception to a person |
| Permission boundary | Weak | Static | Role-based, defined before deployment |
| Connection to systems | Output pasted by hand | Single-task script | Built on live quoting, scheduling, reporting and finance systems |
| Who decides | Unclear | Nobody, until it fails | Your team confirms; every step is logged |
The three we built first.
Quoting Agent
From specifications and drawings to a priced draft quote, built on our automated quoting engine.
- ■Reads: drawings, schedules, specifications, product rules
- ■Produces: draft quote with confidence flags
- ■You confirm: pricing, margins, release
Scheduling Agent
When plans change, it traces the dependencies and proposes a controlled re-sequence.
- ■Reads: sequences, dependencies, crews, deliveries
- ■Produces: proposed re-sequence and conflict warnings
- ■You confirm: the new schedule, before it lands
Reporting Agent
Live operational and financial data assembled into stakeholder-ready report drafts.
- ■Reads: live project, cost and progress data
- ■Produces: report drafts with narrative summaries
- ■You confirm: sign-off before anything is issued
Every agent stands on a running system.
No agent here floats free. Each one extends a system already proven in live use, so its data, permissions and outputs are already part of an operating workflow.
Drawings in.
Structured data out.
Plans, specifications and contracts are where construction data hides. The document intelligence layer parses them into structured records — the shared foundation under every agent in the suite.
It doesn't claim accuracy. It scores its own confidence on every extraction, and routes each record accordingly: high goes to the system, medium goes to a person, low is escalated.
The sentence that quietly becomes a commitment.
Construction disputes are rarely built on contracts alone. They are built on ordinary emails: a date promised without conditions, a duration read as a guarantee, a claim keyword answered casually. The Email Review Agent reads outbound correspondence before the client does — and it never sends or silently edits an email.
A claim trigger, a procedural obligation or an unapproved commitment
The email is held; management or legal approval is required
A commitment that needs conditioning before it goes out
The sender applies the rewrite, or accepts the risk knowingly
Wording that could be clearer but carries no exposure
Optional; the sender decides
What the reviewer actually sees.
Not a score — the sentence it objected to, the rule that caught it, the reason in commercial terms, and a version that says the same thing without creating the exposure. Sample output from live use inside DDDI Group; the correspondence is ordinary site email with nothing identifying in it.
“…which is scheduled for delivery before next Wednesday.”
Commits to a third-party delivery time with no conditions attached. If it does not arrive, this invites complaint and a liability argument — and no project fact currently supports the date.
“…which is currently scheduled for delivery by [CONFIRM: date], subject to supplier delivery and site conditions.”
“The concreting stage is expected to take about two weeks.”
States a duration without its prerequisites — weather, site access, materials, inspections, trade sequencing. It must be conditioned so it cannot be read as a guarantee.
“The concreting stage is currently expected to take approximately two weeks, subject to weather, inspections and trade availability.”
It also says what it could not check.
The review limitations panel is part of the output, not a disclaimer bolted on at the end. A reviewer that cannot see the contract, the programme or the approved scope says so — rather than implying the draft was verified against them.
Built for accountable AI deployment.
Every agent is deployed inside an accountable workflow: what it may read, what it may produce, who confirms it, what gets logged, and where exceptions go.
Defined data boundary
What the agent can read, where it runs, what never leaves.
Role-based permissions
The agent sees what the role it serves would see. No more.
Human confirmation
Commercial, legal and site-critical outputs are approved by people.
Audit logs
What was read, produced and confirmed is traceable.
Exception routing
Anything the agent isn't sure of goes to a person, not a guess.
Staged rollout
Shadow, then assisted, then routine. Never big-bang.
Proven on our own projects first.
The quoting agent runs in live deployment inside the group. Every agent ships the same way: shadow first, then assisted, then routine — with human confirmation designed in from day one.