gray reserve
Pillar 02 · AI & Automation

The AI layer most firms
outsource or fake.

We build it into the engine from the first day. Custom agents, workflow automation, audience augmentation, content orchestration across multi-agent pipelines — owned, monitored, and tuned by the team that runs your marketing.

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What you get

Agents that run,
workflows that compound.

Five AI and automation disciplines, each running in production for our own firm before we ship them to yours. Dogfood-first, always.

Custom AI Agents

RAG pipelines, tool use, MCP integrations. Agents that actually do the work — not demo-ware in a sandbox.

Workflow Automation

n8n, Make, Inngest durable functions. Multi-step orchestration with retries, branching, human-in-the-loop.

Audience Augmentation

Proprietary data reservoirs. Your past buyers, intent signals, and compounding lookalikes — refreshed weekly.

AI Content Engine

An orchestrated multi-agent pipeline. Research, editorial, and strategy agents produce long-form briefings at a scale no agency retainer can match.

Conversational Funnels

AI chat that qualifies, books, and escalates. Integrated with your CRM, your calendar, your Slack.

Monitoring + Guardrails

Cost caps, hallucination checks, eval harnesses, Slack alerts. Because unmonitored AI is a liability, not a system.

Orchestration

Specialized agents,
routed by intent.

Every task hits the agent best suited for the job. Fast agents for routing and transforms. Reasoning agents for long-form drafting. Strategy agents for architectural calls. The routing logic is proprietary — and it's why the engine runs at a fraction of what retainer agencies bill.

  • ✓Real-time telemetry per agent, per task
  • ✓Automatic fallback and retry on agent failure
  • ✓Eval harness runs on every prompt change
See the orchestration layer
ai.grayreserve.com / agents Running
Active AI Agents 147 actions today · All systems nominal · 99.98% uptime
All 24h 7d
Actions today 147 +23
Agents online 4 / 4 Live
Uptime 30d 99.98% SLA
  • •
    Routing Agent Live · 247 tasks · avg 0.8s
    Healthy Live
  • •
    Editorial Agent Queued · 12 drafts ready · avg 14s
    Healthy Live
  • •
    Intelligence Agent Complete · 3 briefs done · avg 48s
    Healthy Live
  • •
    Outbound Personalizer Active · 84 emails · avg 6s
    Healthy Live
Slack alert: Routing Agent completed 247 decisions in 3m 12s
Engagement timeline

Four steps. Not four months of research.

The AI work gets misscoped constantly because nobody wants to commit. We scope hard, build fast, and put it in production where the numbers can argue.

  1. 01

    Map Agents

    Which tasks should AI do, which should humans do, which should never be automated. The hard architectural decisions before any code gets written.

    Week 1
  2. 02

    Build

    Prompts, tools, RAG layers, workflow steps, cost caps, guardrails. Every agent shipped with an eval harness and a rollback plan.

    Weeks 2–3
  3. 03

    Deploy

    Production wiring, Slack notifications, dashboards, cost alarms. A soft launch with real traffic but a human approval gate until trust is earned.

    Week 4
  4. 04

    Monitor

    Evals running on every prompt change. Cost and latency tracked per agent. Weekly reviews of what drifted, what improved, and what should graduate to full autonomy.

    Ongoing
Proof

Running live in our own firm.

147 Agent actions today Across routing, writing, reasoning, outbound, and content
4 Agents in production Routing, editorial, strategy, and outbound — all orchestrated together
99.98% Platform uptime Zero incidents across 12 consecutive months
Stop paying consulting retainers for AI that never ships. Schedule a Briefing

Frequently Asked Questions

What does Gray Reserve actually build with AI and automation?
Gray Reserve builds custom AI agents, RAG pipelines, MCP integrations, and multi-step workflow orchestration using tools like n8n, Make, and Inngest. Every system ships into production — the firm runs the same infrastructure internally before deploying it for clients.
How long does it take to get an AI agent running in production?
Most engagements reach a production-deployed agent in four weeks. Week one maps which tasks AI should own. Weeks two and three build the agent with eval harnesses and rollback plans. Week four handles production wiring, dashboards, and cost alarms.
What AI providers and models does Gray Reserve use?
The firm runs Claude (Anthropic) as the primary reasoning backbone, with routing logic that directs tasks to the correct model tier based on complexity and cost. Haiku handles high-volume transforms, Sonnet handles deep reasoning, and Opus is reserved for architecture decisions. No vendor lock-in — the orchestration layer is model-agnostic.
Can we get AI automation without replacing our existing stack?
Yes. Gray Reserve designs AI layers as additive integrations over your existing CRM, email, and ops tools rather than replacements. The typical entry point is a workflow automation layer that eliminates repetitive manual tasks, with custom agents added as trust and performance data accumulate.
How is ongoing performance monitored after launch?
Every deployed agent runs an eval harness that fires on every prompt change. Cost and latency are tracked per agent in real time. Weekly reviews cover what drifted, what improved, and what should graduate to full autonomy — with Slack alerts for any anomaly before it compounds.

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Fifteen minutes with us. No cost. No deck. Only the mathematics of what your current operations are leaving on the table.

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