◉ LAS VEGAS · EST. 2014
SERVICES · VOL. 11
3 PRACTICES · 50+ INTEGRATIONS
SERVICES THAT SHIP.
Three ways we make it work. Marketing automation. AI integrations. Multi-agent orchestration. Pick one or stack them. Every engagement ends with something running in production.
01 / PRACTICES
Three Ways We Make It Work
◆ SVC · 03
01 · MARKETING
Marketing Automation
Campaigns that trigger, nurture, and close, on autopilot. CRM integrations, lead scoring, and workflows built to scale without adding headcount.
- CRM + lifecycle workflows
- Lead scoring & routing
- Campaign attribution
- Deliverability rebuilds
READ MORE↓
◆ 02 · AI AI Automations
Connect AI models to real business logic. Intelligent triggers, conditional workflows, systems that adapt without breaking.
- Model-to-CRM pipelines
- Conditional workflows
- Guardrails & evals
- Cost & latency budgets
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◈ 03 · ORCHESTRATION Multi-Agent Orchestration
Bridges that let agents hand off tasks, share context, and trigger actions across systems that were never designed to talk.
- Agent handoff protocols
- Shared context stores
- Cross-system triggers
- Observability & logs
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◇ 02 / PRACTICE
Marketing Automation
◆ MKT · AUTO
What we build
- End-to-end CRM lifecycle workflows (HubSpot, Salesforce, ActiveCampaign, Klaviyo, Customer.io)
- Lead scoring + routing logic that sales actually trusts
- Campaign attribution stitched across ads, web, CRM
- Deliverability rebuilds for senders with reputation problems
- Migration projects between platforms (with data hygiene baked in)
Sample timeline · 6 weeks
- WK 1–2 · Discovery, audit, scope lock.
- WK 3–4 · Build core workflows + integrations.
- WK 5 · QA + shadow run with real traffic.
- WK 6 · Cutover + handoff + docs.
◉ TYPICAL ENGAGEMENT
4–8 WKS
Most marketing automation builds ship in this range. Discovery is fixed at 2 weeks; build varies with stack complexity.
SCOPE A BUILD→Common questions
Q · 01
How long does a typical marketing automation build take?
Most marketing automation builds ship in 4–8 weeks. We start with a 2-week Discovery Sprint to map your stack and lock the scope, then build and roll out in tight phases.
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Q · 02
Do you replace our marketing tools or work with what we have?
We work with what you have. HubSpot, Salesforce, Klaviyo, Customer.io, ActiveCampaign. If it has an API, we can connect it. We only recommend new tools when the existing stack physically can't do the job.
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Q · 03
What does a 'campaign attribution' build look like?
We connect your ad platforms, CRM, and analytics so every closed-won deal has a clean source attached. UTM hygiene, server-side events where needed, and dashboards your team will actually open.
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03 / PRACTICE
AI Automations
◈ AI · ML
What we build
- Model-to-CRM pipelines (classification, summarization, enrichment, routing)
- Conditional workflows that branch on model outputs with deterministic guardrails
- Eval harnesses + cost & latency budgets so quality doesn't drift silently
- Staged rollouts: shadow mode → assisted → automated
- Internal copilots tightly scoped to real workflows (not generic chat)
Sample timeline · 8 weeks
- WK 1–2 · Discovery + eval harness setup.
- WK 3–5 · Build pipeline + prompts + tools.
- WK 6 · Shadow mode against production traffic.
- WK 7 · Assisted rollout with human review.
- WK 8 · Full automation + monitoring.
◉ TYPICAL ENGAGEMENT
6–10 WKS
AI builds carry an evaluation overhead. We don't ship AI without measurable quality gates and rollback paths.
SCOPE A BUILD→Common questions
Q · 04
Are AI automations production-ready or just prototypes?
Production-ready. We build with cost budgets, latency targets, eval harnesses, and guardrails. Every AI integration goes through staged rollout (shadow mode, then assisted, then automated) so failures don't hit customers.
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Q · 05
Which AI models do you build with?
Whichever fits the job and the budget. Claude, GPT, Gemini, open-weight models on managed inference. We pick based on cost, latency, and quality benchmarks for the specific task, not vendor preference.
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04 / PRACTICE
Multi-Agent Orchestration
◇ ORC · A2A
What we build
- Agent-to-agent handoff with structured outputs and shared context
- Cross-system triggers (CRM → research agent → drafting agent → human review)
- Tool registries with deterministic execution layers
- Observability dashboards: full trace, cost-per-run, success rates
- Failure modes mapped, retried, escalated; never silently dropped
Sample timeline · 10 weeks
- WK 1–2 · Workflow mapping + agent decomposition.
- WK 3–6 · Build agents + tool layer + context store.
- WK 7–8 · Integration testing + trace dashboards.
- WK 9–10 · Staged production rollout.
◉ TYPICAL ENGAGEMENT
8–12 WKS
Orchestration is the deepest practice. We only take these on when there's a clear, repeatable workflow worth automating end-to-end.
SCOPE A BUILD→Common questions
Q · 06
What does multi-agent orchestration actually mean?
Two or more AI agents handing off work to each other and to humans, with shared context, guardrails, and observability. Sales-ops research → drafting → human review → CRM update is a typical pattern.
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Q · 07
How do you keep agent systems from going off the rails?
Tight scopes, structured outputs, deterministic tool calls, retry logic, and full traces. Every action is logged. Every cost is tracked. You see exactly what the agents did and what they spent.
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Ready to
ship something?
Start with a free consultation, or jump to a 2-week Discovery Sprint. Either way, you'll know what to build, what it'll cost, and how fast it'll ship.