Agentic Solution Accelerators
Reusable, controls-ready building blocks for agentic automation. Each one is extracted from a system we built — most of them running in production today — so your first automated process goes live in weeks, with the approvals, guardrails and audit trail already in it.
Three proven in production, one built and awaiting commissioning, two in development. We say which is which.
Proven in production
Reads incoming documents — invoices, statements, applications, engineering packages — with vision OCR and structured extraction, validates every field against your rules and source systems, and routes exceptions to a reviewer with the evidence attached.
Built from our document-intelligence systems for telecom engineering and financial document validation.
Proven in production
An agent that answers from your knowledge base, SOPs and tickets and cites its sources — as a customer-facing API, an agent-assist panel, or an embedded widget — with a knowledge-gap report that shows what it could not answer and why.
Built from Cortex, our multi-tenant RAG platform running in production for LiveHelpNow.
Built · pre-production
An agent that reads live systems through tools and proposes actions, while execution stays behind a named approver, a role allowlist, a rate limit, a kill switch and an audit log. For operations where a wrong write is expensive.
Built from the operator console we delivered for an automated 36-axis industrial line — running against a test-bench controller while the line awaits commissioning.
Proven in production
A regression harness for agents: a fixed evaluation set, deterministic checks, a second-model judge and end-to-end tests that must pass before a prompt, model or tool change is promoted. Change management for the part of the system that is not code.
Combines three things we run today: the regression gate that protects the aeocontent.ai scoring core, the second-model judging in our RAG systems, and the end-to-end suites from our payments work.
In development
Automates the controls work itself: collects evidence on schedule, matches change tickets to deployments, prepares user-access reviews, and flags exceptions for the control owner — producing workpapers a tester can reperform.
Designed with SOX practitioners around ITGC and ITAC test procedures.
In development
Matches transactions across systems, clears what agrees within tolerance, and hands the rest to a person with a proposed resolution and the supporting records — with completeness and accuracy checks on every batch.
Drawing on a decade of batch closing, deposit files and settlement flows in payments.
Not a slide deck and not a black box — a working system and the paper that lets you rely on it.
The agents, orchestration, integrations and approval points — drawn for your systems, not a generic diagram.
A running implementation you own: agents, workflows, connectors, review UI and infrastructure as code.
Risks, the ITGCs relied on, the ITACs built into the process, and how each one is evidenced and tested.
The fixed evaluation set and end-to-end tests that gate every future change to prompts, models and code.
Monitoring, alerting, failure and recovery procedures, and who is paged for what.
API-first by design, so it can sit behind the automation platform you already license or run code-first on your cloud.
A typical first process. Timelines depend on system access and how many exceptions the process really has.
Why controls come first
Most agent pilots stall at the same point: the demo works, and then risk, internal audit or the external auditor asks who approved what, which version made the decision, and how anyone would know if it went wrong. Our accelerators answer those questions in the design — mapped to ITGCs and with ITACs inside the workflow — which is why they reach production.
Controls-ready automation →Agents, the orchestration that runs them, and the controls that make them auditable.
Flagship capability
AI agents that do real work, coordinated with your systems, automations and people — durable, observable, human-in-the-loop.
How we build agents →Flagship capability
Engineered against IT general controls, with application controls and an evidence trail built into every workflow.
How we make it auditable →Tell us the process, the systems it touches and who signs off on it. We'll tell you which accelerator fits — or that none does.