AI agents and automations, deployed on your systems in weeks — not quarters
We design, build, and operate AI agents that do real work inside your existing systems — with human review on anything that matters. First working agent in about two weeks, on a fixed-scope, fixed-fee sprint.
Book a 30-minute scoping callWhat an AI agent actually is
Strip away the hype and an AI agent is a piece of software that uses a large language model to read, decide, and act inside a workflow — instead of just chatting. It can open a document, pull the fields that matter, look something up in your database, draft the response, and hand the result to a person for approval. The model supplies the language and judgment heuristics; ordinary, testable code supplies the connections to your systems and the rules about what the agent may and may not do.
That last part is the difference between a demo and a dependable tool. An agent with defined inputs, scoped permissions, logged actions, and a human checkpoint is automation you can audit. An unbounded chatbot pasted into a business process is a liability. We build the first kind.
What we deploy fast
Agents that read, classify, summarize, and file documents — intake paperwork, records requests, invoices, permits — and route them with an audit trail.
Agents that pull from your databases and ERP, assemble recurring reports, flag anomalies, and draft the narrative — so the monthly packet stops eating a week.
First-pass handling of inbound email, forms, and requests: extract the facts, categorize, draft a response, and queue it for a person to approve.
Research, drafting, illustration, and publishing pipelines that run on a schedule with editorial guardrails — the same kind we run for our own brands daily.
Agents that move data between systems that do not talk to each other — re-keying, reconciliation, and copy-paste work handled by software instead of staff.
Chat assistants wired to live ERP-derived data with tool calling, so staff ask plain-English questions and get grounded answers — not hallucinations.
How we build
We pick a single, high-friction workflow and ship an agent for it. No platform project, no six-month discovery phase.
Consequential outputs — anything sent, filed, or paid — get queued for human approval. Agents draft; your people decide.
Agents connect to what you already run. We use model APIs under no-training terms, and can deploy in your tenant or on-premises.
A working agent on real data in about two weeks, then iterate. You judge results on your own workload, not a demo.
We don’t just advise — we run our own business on AI agents
Every recommendation we make is something we already live with in production. These are our own systems, built and operated by us — not client anecdotes:
We built and operate Ask Civic AI, the OpenAI-powered assistant inside our Civic Suite municipal platform. It answers staff questions about budgets, permits, and operations through a read-only tool contract over ERP-derived data — grounded in the numbers, not guesses. The full architecture, including what runs on demo data today, is documented on our how we use AI page.
An agent pipeline that researches, writes, illustrates, and publishes a new article every weekday, then promotes it on an absolute schedule. Live since June 2026: 43 of its first 44 runs succeeded, with editorial guardrails and zero manual steps on a normal day.
Our portfolio of 13 production websites runs on one cluster through one automated path: CI/CD, SEO verification, content, and monitoring. Agents draft the changes and drive the checks green; protected branches, required tests, and a human merge gate every release.
Lead-generation and enrichment engines with signal scoring and ML-style learning loops run our own pipeline in production — discovering, enriching, and prioritizing prospects continuously.
Every one of those claims is documented at the architecture level, with the tool contracts, security boundaries, measured scheduling data, and the failure modes we hit along the way: read how we use AI.
Behind the agents is 15+ years of software engineering — .NET, React, SQL Server — led by founder James C. Jordan in Florence, SC. Agents that touch production need engineering discipline, and that is the discipline we bring. Read more about Innovation Nexus.
Who it’s for
Businesses drowning in documents, reporting, intake, or data entry — and local governments facing the same workload with public-records rules on top. For cities and counties we bring specific domain depth: see AI consulting for local government, the fixed-scope AI readiness assessment, and AI document & records automation. If your town needs rules before tools, start with the free AI use policy template.
For the full picture of our AI practice — strategy, agents, LLM product development, and governance — see the AI consulting overview.
The AI Agent Sprint
A fixed-scope engagement with a working agent as the deliverable — not a report:
- Discovery call (30 minutes). We pick the one workflow with the best effort-to-payoff ratio and define what “working” means for it.
- First working agent (~2 weeks). Built on your systems and your real data, with guardrails and human review in place from day one.
- Iterate. Tighten accuracy, widen scope, or add the next workflow — each step judged by results on live work.
The sprint is a fixed fee, scoped on the 30-minute call — you know the price before we start.
Frequently asked questions
How long does it take to get a working AI agent?
For a single, well-scoped workflow, the first working agent is typically running on your systems in about two weeks. We start narrow on purpose: one workflow, measurable output, human review in the loop. Broader rollouts iterate from that working baseline rather than from a slide deck.
Will our data be used to train AI models?
No. We build agents so your data stays in your systems, and we use model APIs under terms that exclude training on your inputs. Where requirements demand it, agents can run in your own cloud tenant or on-premises, and every consequential output is reviewed by a person before it leaves the building.
What does an AI Agent Sprint cost?
The sprint is a fixed fee, scoped on a 30-minute call. Price depends on the workflow, the systems the agent must connect to, and the review requirements — you know the number before any work starts, and there is no open-ended hourly meter.
Will AI agents replace our staff?
No. Agents remove the repetitive part of the work — retyping, copying between systems, first-draft writing, routine triage — so your people spend time on judgment, review, and the work that actually needs a human. Consequential decisions keep a human in the loop by design.
Ready to see an agent on your own workflow?
Book a 30-minute scoping call with Innovation Nexus LLC. We’ll pick the workflow, fix the fee, and ship the first working agent in about two weeks.
Book a scoping call