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Service · 07 · AI Automation · New

Custom AI agents. Working while you sleep.

We design, ship, and run bespoke AI agents that handle the operational work humans shouldn't be doing — lead qualification, content velocity, customer support, internal ops. Days to deploy, not quarters.

  • 2–6 wks Scope to first agent live
  • 0 Markup on your API costs
  • 24/7 Agents in production
01 · The new operating model

Your competitors deployed agents last quarter.

AI is already in production at your competitors. Lead-qualification agents triaging while their sales reps sleep. Content agents shipping at 10× the cadence. Internal ops agents running compliance checks on autopilot. The gap is widening every week.

The old playbook

Humans on the volume.

Five hires to run lead-routing. Three more for content moderation. Two more for compliance. Burnout, attrition, and a budget that scales with your bookings.

  • Operating modelHire-and-train
  • CostLinear with volume
  • CoverageBusiness hours · weekdays
The Matrixe playbook

Agents on the volume.

Custom AI agents handle the repetitive, observable work. Senior humans handle judgment. The system gets cheaper per unit of output every quarter — and you stop hiring for the operational layer that compounds linearly with your bookings.

  • Operating modelBuild-once · run forever
  • CostFlat with volume
  • Coverage24/7 · auditable

This isn't ChatGPT for your team. It's specialized agents in your accounts, doing real work.

02 · What we ship

Specialized agents. One operating system.

Not "AI tools." Specialized agents wired into your stack — running 24/7, gated by humans on judgment calls, audited daily.

01

Custom agent architecture.

Bespoke orchestrations designed around your ops, your data, your stack. Not no-code templates — production agents with memory, tool access, retries, and human-in-the-loop gates.

  • Memory · vector DB
  • Tool calling
  • Human gates
  • Observability
  • Cost capping
  • Auditable logs
02

Lead qualifier.

Triages every inbound, enriches with firmographic + behavioral data, scores against your ICP, routes hot leads to humans within 30 seconds.

03

Content velocity agent.

Briefs from keyword data, drafts from your style guide, runs through a fact-checker, queues for senior review. Articles shipping at AI velocity, no quality drift — every piece signed off by a human editor before it goes live.

04

Customer support agent.

Answers tier-1 / tier-2 tickets from your knowledge base + product docs, escalates everything else cleanly. Recovers a meaningful share of human-hours on the predictable end of the queue.

05

Anomaly watcher.

Monitors your dashboards 24/7. Detects CPM spikes, ROAS drops, conversion anomalies, attribution gaps — and pings the right human on Slack before it costs you a quarter.

06

Predictive analysis.

Cohort-level forecasts on retention, LTV, churn, and pipeline conversion. Backed by your data warehouse, validated weekly.

07

Internal ops agents.

Compliance reviews, contract redlines, expense triage, vendor onboarding. Every back-office bottleneck where humans hate the work and the work is mostly pattern-matching.

08

Integrations & observability.

Slack, HubSpot, Salesforce, Linear, GA4, Stripe, Notion, Sanity — every agent wired into your real systems with logs, retries, and cost dashboards you can actually read.

03 · How we ship agents

Scope to live. 2–6 weeks.

A senior-led, sprint-based engagement that ships a working agent in your accounts — not a 60-page strategy deck.

  1. Week 1 01

    Audit.

    Map the highest-leverage ops to automate. Score by hours-saved × stakes × feasibility. Pick the first agent — the one that pays for the engagement.

  2. Week 2 02

    Design.

    Agent architecture, prompts, tools, memory, retries, escalation paths, cost caps. Reviewed by senior engineers. Specced before a single API call is made.

  3. Weeks 3–4 03

    Build.

    Agent shipped to your accounts. Integrated with your stack. Trained on your data. Logs streaming to a dashboard you can read. Live within 4 weeks.

  4. Ongoing 04

    Operate.

    Performance monitored daily, prompts tuned weekly, cost-per-task tracked per run. New agents added when the next bottleneck surfaces. The stack compounds.

04 · Stack

Frontier models. Production plumbing.

We use whichever model wins for your task — Claude, GPT, Gemini, Llama — wired through the orchestration and observability layer your engineers will actually trust.

Models
  • Claude Sonnet · Opus
  • GPT-5 · GPT-5 Mini
  • Gemini · Llama
  • Custom fine-tunes
Orchestration
  • n8n · Make
  • LangGraph · Mastra
  • MCP servers
  • Custom Python / TS
Memory & retrieval
  • Pinecone · Weaviate
  • Postgres · pgvector
  • Cloudflare Vectorize
  • Document parsers
Observability
  • Langfuse · Helicone
  • Cost dashboards
  • Prompt versioning
  • Eval suites
06 · Engagement

Start small. Scale on proof.

Most engagements start with one high-leverage agent — the one that pays for the build in 90 days. Once it's running, we expand the stack. No annual contracts. API costs billed to your account directly.

Talk to an AI architect
Single agent 2–4 weeks
  • Audit · pick the highest-leverage ops
  • One agent designed + shipped
  • Integrated with your stack
  • Observability dashboard
  • 30-day operate & tune
Fixed fee · scoped on call
Agent stack Ongoing
  • 3–7 agents in production
  • Daily monitoring + tuning
  • Weekly war-room calls
  • New agents added quarterly
  • Outcome-tied bonus
Monthly · cancel anytime
07 · Questions

AI Automation questions people ask.

Honest answers from senior operators. No "AI will solve everything" hype-speak.

  • 01 Who pays for the API costs?

    You do — directly. The API keys (Claude, OpenAI, Gemini) live in your accounts. We configure, run, and tune; you see exactly what each agent costs per task. Typical per-task cost: $0.02–$0.40 depending on complexity. We optimize cost-per-task as part of the engagement.

  • 02 How long until the first agent is live?

    2–6 weeks from kickoff to a working agent in your accounts. Simple use cases (single tool, narrow scope): closer to 2 weeks. Complex orchestrations with multiple integrations + memory: 4–6 weeks. Anyone promising "deployed tomorrow" is selling you a Zapier zap.

  • 03 Can we start with just one agent?

    Yes — that's how every engagement starts. We pick the single highest-leverage agent first (usually lead-qualification or content velocity). Ship it, prove the ROI, then scale the stack. No annual lock-in, no "platform fee."

  • 04 How is this different from Zapier or Make?

    Zapier is if-this-then-that. Our agents reason: they decide which path to take, call multiple tools, retry on failure, escalate when uncertain, and remember context across runs. We use n8n / Make for the deterministic glue, custom agent code for the judgment.

  • 05 Do you train our team on the system?

    Yes. Every engagement includes a handoff sprint — your engineers learn the orchestration, your operators learn to read the dashboards and tune prompts. The system is yours, full stop — we don't gatekeep what you paid us to build. Most clients keep us on for ongoing tuning and new agents; the ones who go in-house take the stack with them and ship from day one.

  • 06 What about data privacy and access?

    Mutual NDAs and DPAs at kickoff. Models routed through zero-retention endpoints (Anthropic, OpenAI, Azure all support it). Your data stays in your databases; agents call APIs in your accounts with scoped tokens. We've passed enterprise security reviews at publicly listed clients on this exact setup — happy to share the architecture document on request.