GAT Solutions

AI consulting · Adoption · Engineering

Put AI inside the operating workflow—not beside it.

GAT helps teams adopt Claude, Claude Cowork, Claude Code, ChatGPT, and Agentforce; connects them to the right Salesforce and go-to-market data; and builds the RAG, chatbots, agents, rules, approvals, evaluations, and handoffs required for production work.

Book an AI consultationTrace a lead end to end ↓

Revenue system trace · new qualified inquiry

One event, eight controlled handoffs, one source of truth.

RuleAIHuman
  1. 01Rule

    Capture

    Create the lead and preserve its source

    Form / HubSpot

  2. 02AI

    Enrich

    Resolve the company and useful context

    Data services

  3. 03AI

    Qualify

    Interpret need, fit, and buying signal

    Salesforce + AI

  4. 04Rule

    Route

    Apply territory, segment, and capacity rules

    Salesforce

  5. 05AI

    Brief

    Give the owner context before first contact

    Claude / ChatGPT

  6. 06Human

    Follow up

    Draft the next message and create the task

    Sales + marketing

  7. 07Rule

    Update

    Write the approved outcome to the record

    Salesforce

  8. 08Human

    Surface

    Show pipeline, attribution, and exceptions

    Revenue reporting

Salesforce records the state. Other systems can trigger, interpret, or act, but ownership and reporting remain explicit.

Inspect every decision · design every fallback

AI engineering trace

One accountable consultant → governed gateways → metered outcomes

human operated
Claude

Accountable operator

Senior GAT consultant

GTM Systems EngineerAI EngineerArchitect
ChatGPT

AI drafts, retrieves, and executes tools; the consultant directs, reviews, and owns every write.

ApexGenius · Salesforce MCP
Custom MCP servers + APIsOAuth · tiered write gating

The client's systems stay the source of truth

CRMSalesforce org
ClinicalEHR records
VoiceFive9 telephony
Automationn8n
AnalyticsData warehouse

Metered, not claimed

47 orgs · 2,645 metered calls

ApexGenius MCP gateway in production

92,000+ chunks · 16,550 answers

RAG corpus serving governed answers

HIPAA-conscious translation

Gemini workflow inside a healthcare org

114 tools · tiered write gating

Custom MCP server — reads free, writes gated

59 built · 21 live

n8n workflows running client operations

Consultant runs every sessionGateways scope every writeOutcomes are metered, not claimed

Choose the operating model

Three ways AI can work with Salesforce

The model is not the architecture. Where people work, where the data lives, and where actions happen determine the right pattern.

Assistant-led

Salesforce inside Claude or ChatGPT

Your team works from the AI assistant it already uses while permission-bound Salesforce data and approved actions are available through MCP.

Salesforce MCP consulting →Claude + Salesforce →ChatGPT + Salesforce →
Best when
Research, record questions, meeting briefs, admin support, drafting, and guided record updates.
What GAT designs
Identity and permission design, tool access, prompts, approval gates, testing, rollout, and adoption.

Salesforce-native

Agentforce inside Salesforce

AI works within the Salesforce experience, using platform data, topics, actions, and handoffs that fit the way sales and service teams already operate.

Agentforce consulting →
Best when
Employee assist, service resolution, guided selling, and repeatable processes that should stay native to Salesforce.
What GAT designs
Use-case scope, data readiness, topics and actions, guardrails, evaluation, deployment, and operating ownership.

Cross-system

AI workflows across the GTM stack

An event can begin in a form, product, support, or marketing platform; AI interprets the context; automation moves the work; Salesforce records the state.

Salesforce integrations →Automation sprints →
Best when
Lead routing, attribution, customer onboarding, case operations, renewals, and workflows spanning multiple platforms.
What GAT designs
System architecture, APIs and integration contracts, identity resolution, orchestration, exception handling, and monitoring.

Decision design

Rules enforce. AI interprets. People own the consequential calls.

A dependable workflow does not ask AI to do everything. It assigns each kind of decision to the control that can handle it best.

Known conditions

Rules enforce

Can the decision be written as a stable if/then?

  • Deduplicate by agreed identifiers
  • Apply territory and ownership rules
  • Start SLAs and create required tasks

Unstructured context

AI interprets

Does the step require language, context, or judgment?

  • Classify intent from an inquiry
  • Summarize account and case history
  • Draft a response from approved context

Consequential choices

People own

Does the decision create risk, commitment, or an exception?

  • Approve customer-facing communication
  • Resolve strategic-account conflicts
  • Override policy with accountable judgment
System-of-record write

Salesforce changes only after the relevant rule, AI interpretation, and approval have passed. The workflow writes the result and the context needed to understand it later.

Governance buyers can inspect

Control the workflow before the workflow controls the risk

Governance becomes useful when it answers practical questions about access, actions, approvals, evidence, failure, and ownership.

We document these decisions as part of the architecture—not as a policy appendix after launch.

Access boundaryWho can see which data?
Named identities, least-privilege permissions, and explicit object and field boundaries determine what is available to each workflow.
Action boundaryWhat is AI allowed to do?
A short allowlist defines available tools and actions. Read, draft, recommend, and write permissions are treated as separate choices.
Decision boundaryWhen must a person approve?
Approval gates sit before consequential messages, commitments, destructive changes, and exceptions—not after the action has happened.
Audit trailCan we reconstruct what happened?
The workflow records its input, decision path, action, result, and owner so the team can review behavior without reading minds.
Failure pathWhat happens when it is wrong?
Test cases, confidence thresholds, exception queues, monitoring, and a rollback or revocation path are designed before launch.
Operating ownerWho owns it after launch?
A business owner owns the outcome, a system owner owns reliability, and both receive a clear operating playbook.

Business systems we build

Start with the work that needs to move

AI is one layer of the system. The business case usually lives in response time, handoff quality, operating capacity, visibility, or platform simplification.

Revenue operations

Turn demand into owned pipeline

Operating result

Faster response, fewer dropped handoffs, and pipeline reporting leaders can trust.

  • Lead intake, enrichment, scoring, and routing
  • HubSpot-to-Salesforce source and attribution architecture
  • Rep briefs, follow-up orchestration, and SLA alerts
  • Pipeline hygiene, inspection, and forecast exceptions

Customer operations

Run cases as one connected process

Operating result

More consistent service, clearer ownership, and less manual case administration.

  • Case intake, classification, assignment, and escalation
  • Service Cloud connected to portals and support applications
  • Case summaries, knowledge retrieval, and response drafts
  • Customer onboarding, document, and renewal workflows

Platform transformation

Change the system without losing the operation

Operating result

A cleaner source of truth, fewer platform seams, and a safer path through change.

  • Salesforce org migrations and org consolidation
  • Data mapping, deduplication, ownership, and cutover planning
  • Finance, product, marketing, and support integrations
  • Operating-model redesign, dashboards, and team enablement

AI engineering

Ground answers and conversations in business context

Operating result

More useful answers, safer automation, and a clear human handoff when the system reaches its boundary.

  • RAG ingestion, retrieval, reranking, and source-aware answers
  • Customer, employee, sales, and service chatbots
  • Authenticated patient-to-nurse chat with routing and audit history
  • Model and tool integration, evaluations, monitoring, and controls

Have a different process in mind? If Salesforce records the customer, case, pipeline, or operating state, we can map the surrounding system.

Bring us the workflow →

From operating problem to operating system

Architecture is only useful when the team can run it

GAT stays accountable through workflow design, implementation, rollout, and the first operating cycle.

  1. Map01

    Start with the operating problem

    We trace the current workflow, handoffs, failure points, owners, systems, and the measure that should move.

  2. Design02

    Assign every decision

    We choose the architecture and make each rule, AI judgment, approval, write, and fallback explicit before build begins.

  3. Ship03

    Build against real scenarios

    We connect the systems, configure Salesforce, test edge cases in a safe environment, and roll out by role and workflow.

  4. Operate04

    Measure and improve the system

    We monitor exceptions, adoption, and business performance; tune what is weak; and leave the team with clear ownership.

Project or product?

Choose the smallest path that solves the real need

GAT delivers custom systems. ApexGenius is the packaged Salesforce MCP product we built for Claude and ChatGPT.

Custom revenue workflow? Work with GAT.

Packaged Salesforce access in Claude or ChatGPT? Start with ApexGenius.

Decision table for choosing a GAT consulting engagement or the ApexGenius product
What you needBest pathWhy
A custom workflow across Salesforce and several platformsWork with GATThis is a systems-architecture and delivery engagement.
Lead routing, attribution, case management, or revenue automationWork with GATThe operating process, data model, integrations, and adoption all need design.
An org migration, consolidation, or Agentforce implementationWork with GATThe work changes your Salesforce architecture and requires managed delivery.
Salesforce available inside Claude or ChatGPT through a packaged MCPStart with ApexGeniusUse the product when the connection is the need—not a custom transformation project.
Help choosing among MCP, Agentforce, and a cross-system workflowBook a GAT consultationWe will map the use case and recommend the smallest architecture that fits.
Book a ConsultationExplore ApexGenius →

Salesforce + AI resources

Pressure-test the architecture before the build

Use the field guides to frame production readiness, choose among Agentforce, MCP, and RAG, or map the service system behind a chatbot.

Browse every resource →
Playbook9 min read

Salesforce AI Production Readiness: Permissions, Evaluation, Approval, and Rollback

A practical readiness framework for moving a Salesforce AI workflow from an impressive demo to governed production work.

AI + SalesforceRead →
Decision Guide10 min read

Agentforce vs MCP vs RAG: Choosing the Right Salesforce AI Architecture

Separate the user interface, connection, retrieval, action, and governance layers before choosing a Salesforce AI platform.

AI + SalesforceRead →
Architecture9 min read

Salesforce AI Chatbot Architecture: Grounding, Case Creation, and Human Handoff

How to design a customer, patient, or internal service chat that retrieves the right context, creates governed work, and hands risk to a person.

Service + case operationsRead →

AI + Salesforce questions

What buyers ask before architecture starts

What does AI + Salesforce consulting include?
It can include workflow and data architecture, Salesforce configuration, Agentforce, Claude or ChatGPT connections, MCP, cross-system integrations, AI evaluations, governance, rollout, and adoption. We scope the engagement around a business workflow and an accountable outcome—not around a model demo.
Do we need Agentforce to use AI with Salesforce?
No. Agentforce is a strong fit when the experience and actions should live natively inside Salesforce. Claude or ChatGPT over MCP can be a better fit when people already work in those assistants. Cross-system orchestration is often right when the workflow spans Salesforce, marketing, product, finance, or support platforms. We select the architecture from the use case.
Can you connect HubSpot, Salesforce, and marketing attribution?
Yes. We design how source, campaign, contact, account, opportunity, and revenue data move between the platforms; define ownership and deduplication rules; and build the routing and reporting around that model. AI can help interpret unstructured context, but attribution definitions and record ownership remain explicit business rules.
Can you build Salesforce case management and service workflows?
Yes. That can include intake from forms, email, portals, or support applications; classification and assignment; Service Cloud configuration; summaries and knowledge retrieval; escalation paths; customer communication; and reporting. The exact design follows the service model and compliance needs.
Do you handle Salesforce org migrations and consolidation?
Yes. We map the target operating model and data model, inventory automation and integrations, define record ownership and deduplication, plan migration and cutover, test the new org, and support rollout. AI may accelerate analysis and documentation, but migration controls remain deterministic and reviewable.
Can AI safely update Salesforce records?
It can when the workflow is designed for it. We separate the ability to read, recommend, draft, and write; apply the connected user's Salesforce permissions; restrict available actions; add approval before consequential changes; and design logs, monitoring, revocation, and rollback appropriate to the use case.
What is the difference between hiring GAT and using ApexGenius?
Hire GAT when you need a custom operating workflow, architecture, integration, migration, Agentforce implementation, or managed delivery. Use ApexGenius when your need is packaged Salesforce access inside Claude or ChatGPT. GAT built ApexGenius, so we can also help determine where the product ends and custom work begins.

Initial systems consultation

Map the workflow. Assign the decisions. Put AI to work.

Book a ConsultationOr explore ApexGenius
  • You leave with
  • A focused consultation with a senior systems consultant
  • A current-state fit and architecture read
  • A recommended path — implementation, ongoing ownership, or product