Discovery
We sit with the people doing the work. Map the workflow, the data, the constraints. Pick one bet worth running first.
- Stakeholder interviews
- Data + system audit
- Opportunity shortlist
- Success metric — written down
An AI consulting practice Haddonfield, NJ · Est. 2024
In the Age of AI, Be Brilliant.
We help organizations move from curiosity to capability — turning generative AI from a board-deck slide into measurable, shipping work.
§01 · What we do
Four practices, one outcome: AI you can ship.
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Strategy & Roadmaps
An honest map of where AI moves the needle in your business — and where it doesn't. We pressure-test ideas against your data, team, and timeline, then deliver a 90-day plan you can actually execute.
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LLM & RAG Implementation
Production-grade systems that pair the right model with your organization's knowledge. Retrieval pipelines that respect your sources, evaluation harnesses that catch regressions, and a deployment story that survives audits.
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Fine-Tuning & Domain Models
When prompting alone doesn't carry the work, we train. Supervised fine-tuning, preference optimization, distillation to small models — chosen because it fits the problem, not the trend.
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Workflow Automation
Agentic systems and human-in-the-loop tools that take real hours out of real workflows. We instrument every step so the savings show up in a dashboard, not a slide.
§02 · How we work
Three movements. Roughly twelve weeks.
We don't do six-month discoveries. By week four you have a working prototype; by week twelve, a system in production with a measurement plan attached.
Build
A working system in your environment, against your real data. Weekly demos. Every claim has an eval behind it.
- Reference architecture
- Eval suite & baselines
- Pilot deployment
- Handoff documentation
Measure
The boring, important part. We instrument outcomes, train your team, and write the runbook for what comes after we leave.
- Outcome instrumentation
- Team enablement
- Runbook & on-call
- Next-quarter roadmap
§03 · About
A small practice. On purpose.
Brilliant Age is a senior consulting practice for organizations that have decided generative AI matters — and are tired of pilots that don't go anywhere. We're small because the work is technical and the trust required is total; we'd rather do six engagements a year right than thirty wrong.
- 06
- 12w
- Haddonfield
§04 · Selected work
Recent engagements.
A sample of work shipped this year. Client identities withheld; outcomes are not.
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Underwriting copilot for non-standard risks.
Replaced a 90-minute manual file review with a retrieval pipeline trained on a decade of bound submissions. Underwriters keep the keyboard; the system surfaces the precedent and the citation.
- −41min
- 98.7%
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Document discovery at partner-level rigor.
Retrieval-augmented document review with mandatory citation enforcement and partner sign-off built into the workflow. 4,300 documents per matter at half the calendar time, with an audit trail their general counsel approved before the work started.
- −58%
- 99.4%
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Internal support copilot with warm handoff.
Trained on three years of resolved tickets, deployed alongside the existing team. Routes to a human when confidence drops; never when it doesn't need to. Their hardest cases now arrive pre-triaged.
- 38.4%
- +0.6
§05 · Dispatch
Recent notes.
The cheapest model that works is the right model.
We run Haiku before Sonnet, Sonnet before Opus — every time. A defense of starting small, and three production systems where “small enough” turned out to be smaller than anyone expected.
A field guide to evaluations.
The seven evals we ship with every engagement, why “vibes-based” review is a tax you pay forever, and how to write the first eval before you write the first prompt.
Against the pilot.
“Let's run a pilot” is usually the most expensive thing a leadership team can decide. What to do instead — and how to tell when a pilot is the right answer (rare, but real).
§04 · Contact
Ready to be brilliant?
Tell us what you're trying to do. We reply to every inquiry within two business days — usually with a question that sharpens it.