// capabilities · platform engagements

Where we deploy and where we migrate away from.

Enterprise AI platforms have collapsed into three default options. We have a stance on each. Vendor-neutrality is a sales position, not an engineering one.

Salesforce Agentforce

deploy here

Strong fit when CRM is the system of record and the agent's primary tools are inside the Salesforce surface. Native data access, native action gating, native audit trail.

// we accept
  • Customer service triage and case routing inside Service Cloud
  • Renewal workflows where Salesforce CPQ is the source of truth
  • Sales prospecting agents tightly bound to Sales Cloud data
// we avoid
  • Workflows that span Salesforce + 4+ external systems — the orchestration tax leaves the platform
  • Use cases requiring custom guardrail policies beyond the built-in Trust Layer

Microsoft Copilot Studio

deploy here

Strong fit inside the Microsoft 365 + Dynamics surface. We deploy here when the buyer is already standardized on M365 and the agent surface is Teams or Outlook.

// we accept
  • Productivity agents inside Teams (meeting prep, status digest, scheduling)
  • Internal helpdesk routed through Outlook and SharePoint
  • Dynamics-bound CRM and ERP automation
// we avoid
  • Public-facing customer agents — the brand surface and customization are weaker
  • High-volume API workloads — the platform's connector limits surface fast

Google Vertex AI Agent Builder

selective

Strong primitives, weaker product. We deploy on Vertex when the buyer is GCP-native and the workload is data-heavy (BigQuery as the source of truth). We avoid it for workflow-heavy agents where the orchestration story is still maturing.

// we accept
  • BigQuery-backed analytical agents (NL → SQL → result)
  • RAG over GCS-hosted document lakes
  • Workloads where Gemini's long context is a structural advantage
// we avoid
  • Multi-agent topologies — the framework story is behind LangGraph and CrewAI
  • Workflows requiring deep tool ecosystem (still maturing vs. M365 / Salesforce)

LangGraph / CrewAI / custom

deploy here

Our default when the workflow spans multiple systems, requires custom guardrail policies, or has compliance constraints the SaaS platforms can't satisfy. Most of our engagements end up here.

// we accept
  • Multi-system orchestration across CRM, ERP, payments, and external APIs
  • Custom guardrail policies that need to live in version control
  • Regulated industries (insurance, healthcare, financial services)
  • Workflows requiring replayable traces in your observability stack
// decision grid

How we pick.

The questions we walk through on the first discovery call. The order matters — the answer to question one constrains every answer below it.

  1. Q01

    Is the system of record one of Salesforce / Dynamics / BigQuery?

    → Lean toward the native platform (Agentforce / Copilot / Vertex) for the primary integration.

  2. Q02

    Do you need custom guardrails or replayable traces beyond what the platform offers?

    → Build on LangGraph or CrewAI with the SaaS platform as one tool among many.

  3. Q03

    Is the workflow customer-facing with brand surface requirements?

    → Custom front-end + LangGraph backend. The SaaS platforms are weaker at brand control.

  4. Q04

    Is this regulated (insurance / healthcare / payments)?

    → Custom topology. Compliance teams need policies in version control and traces in their observability stack — not in a vendor's black box.

// case studies

Agentforce ↔ LangGraph hybrid in production.

See the case studyBook a session