Maple

What We Build

The agentic stack,assembled.

We don't sell Salesforce add-ons. We assemble the production agentic system that turns your data into a workforce across Salesforce, AWS, Snowflake, Databricks, Maven AGI, Vonage, and Anthropic. Then we govern it after launch.
04
Experience Layer

Vonage · Service / Sales / Marketing Cloud

03
Reasoning + Agent Layer

Anthropic · Agentforce · Maven AGI

02
Data Foundation

Data Cloud · Snowflake · Databricks

01
Cloud Foundation

AWS · Salesforce

Agentic Governance

The Four Layers

Each layer composedfrom the right partners.

The agentic enterprise is layered architecture, not a single product. Each layer has its own concerns, its own platforms, and its own governance.

Where the agent's reality lives.

The Data Foundation

Without a unified, real-time, governance-ready data foundation, every agent above it hallucinates or stalls. We architect the golden record that makes agents trustworthy.

Salesforce Data Cloud · Snowflake · Databricks · AWS

  • Data Cloud zero-copy integrations to Snowflake and Databricks
  • Identity resolution across product, sales, and CS systems
  • Real-time triggers on data events (not nightly batch)
  • Compliance and lineage baked in: HIPAA, SOC 2, GDPR-ready

Where decisions and actions happen.

The Reasoning + Agent Layer

Claude is the reasoning engine. Agentforce and Maven AGI are the runtimes that take action: qualifying leads, resolving cases, orchestrating revenue. Two deployment paths.

Anthropic Claude · Salesforce Agentforce · Maven AGI

  • Native: Claude inside Agentforce via the Salesforce-Anthropic integration: trust-boundary path
  • Standalone: Claude on AWS Bedrock or direct API: for non-Salesforce stacks
  • Maven AGI for L1 deflection: alternative or complement to Agentforce per engagement
  • Industry-tuned reasoning patterns for FinTech, HealthTech, B2B SaaS

Where the agent meets the customer.

The Experience Layer

Per Salesforce's TDX2026 Headless 360 announcement, the experience layer is decoupled from the agent runtime. Agents do their work in Agentforce; the work shows up wherever the customer is.

Vonage · Salesforce Service / Sales / Marketing Cloud

  • Voice + SMS agents via Vonage for compliance-aware outreach
  • Web chat surfaces backed by Service Cloud and Maven AGI
  • Embedded agentic experiences inside your own product UI (via Headless 360 / MCP)
  • Slack, WhatsApp, voice, web: agents show up where the customer is

The Maple flagship: recurring service, not project deliverable.

Agentic Governance

Where most agent deployments quietly fail in year one. Production agents drift, prompts decay, data triggers misfire, and reasoning quality slips. We don't hand off and disappear.

A monthly subscription, governed by Maple

  • Monthly Agent Performance Audits: what each agent did, where it failed, where to retune
  • Prompt + Atlas reasoning-engine optimization based on real conversation data
  • Eval framework + automated regression testing across releases
  • Quarterly business reviews with measurable Agentic ROI
  • Build-Operate-Transfer: full ownership handoff when ready, no vendor lock-in

What "production" means

The architecture isn't the slide deck.

The architecture is how production agents handle five thousand customer events a day in week eighteen of the engagement without a human in the loop.

The Engagement Model

Build. Operate. Transfer.No retainer trap.

Build

Agents and the data foundation in 6 to 10 weeks. Not 9 months.

Operate

Agentic Governance keeps the system improving every month.

Transfer

Your team owns it independently when you're ready.

What We Don't Do

A short, opinionatedfilter.

It costs us a few inbound leads. It qualifies the rest much harder.

  • Generic Sales Cloud rollouts that don't include an agent layer
  • Retainer trap "managed services" that are ticket queues with a different name
  • Software license resale: we architect on the platforms you already pay for

Ready to architect your agentic stack?