Claude AIMarTechHubSpot
HubSpot Prompts Skill for Claude
An installable Claude Skill that makes HubSpot prompt work faster, smarter, and easier to reuse.
- HubSpot prompts packaged
- 80+
- Role-based libraries
- 6
- Prompt workflow modes
- 4
Claude Automated Workflows & Training
Build Claude workflows your team can actually own.
We identify your high-friction work, build Claude-powered workflows, Skills, agents, and integrations around it, then train your team to operate and improve what we ship.
Start with one workflow. We'll help determine whether it needs a Skill, agent, integration—or simply a better process.
What you get
Claude agents that actually ship work—wired into your data and tools through a governed backbone, with your team trained to run and extend them.
Claude agents that actually ship work—wired into your data and tools through a governed backbone, with your team trained to run and extend them.
Workflow Discovery & Mapping
Custom Claude Agents
Multi-Agent Orchestration
MCP & Tool Integration
Shared Memory & Context
Guardrails & Governance
Team Training & Enablement
Runbooks & Documentation
Monitoring & Iteration
Common automation problems we help teams fix
Most teams don't have an AI problem—they have ten AI experiments that never meet. Clever demos, zero leverage, because nothing shares data or hands off to anything else. We fix the connective layer first, then automate responsibly.
Ten tools that don't talk
A chatbot here, a summarizer there, a script no one owns—each works, none share context, so the whole never adds up to a system.
AI pilots that don't stick
Teams try GenAI, but the workflow isn't integrated and adoption stalls once the initial excitement fades.
No shared memory
Every agent starts from zero and a person copies output between tools by hand—so the moment they're busy, everything stalls.
Agents can't reach your data
Without governed access to real systems, an AI agent improvises on stale, fragmented information—and can't be trusted with real work.
No guardrails or ownership
No one owns the source of truth, access, or QA—so a shared backbone becomes a bigger mess and risk grows with every new agent.
You depend on the builder
The automation works until it needs a change, and the only person who understands it is gone—so it quietly rots.
Three principles behind every Claude engagement
We build practical Claude agents wired into a governed backbone—and train your team to own them. That means automating the handoffs that actually cost time, connecting agents to trusted data, and putting guardrails in place so adoption is safe and durable.
One system, not ten tools
Agents share context and write to one governed source of truth, so each one can see what the last one did—and the whole gets more useful as it grows.
Built for real jobs, in your voice
We automate the specific work your team repeats—briefs, triage, extraction, drafting, reporting—shaped to how you actually operate, not a generic demo.
Designed to be owned
Every build ships with runbooks, guardrails, and hands-on training so your team can run, extend, and govern the agents without depending on us.
How an engagement works
Claude agents only create leverage when they run as one system: wired into your data and tools, sharing context, governed, and operable by your team. We build the automations, connect them to a governed backbone, and train your people to run and extend them—so the value compounds instead of stalling after the demo.
1
Map the work
We find the handoffs and repeated tasks worth automating—scored by frequency and blast radius, not by what's flashy—and agree on what 'done' looks like.
2
Build the agents
We build custom Claude workflows for the real jobs: reading, drafting, extracting, routing, and reporting—shaped to your voice, data, and process.
3
Wire to one backbone
We connect agents to a governed source of truth and your tools via APIs and MCP, with shared context—so they hand off to each other instead of running as isolated toys.
4
Add guardrails
We define what's the source of truth, who can write to it, access boundaries, and how you'd know if an agent got something wrong—before scale, not after.
5
Train & hand off
We train your team with runbooks and hands-on enablement so they operate, extend, and govern the agents confidently—without depending on us.
What you'll walk away with
Not a pile of features—four outcomes that compound. A production-ready Claude workflow, connected to the context it needs, safe to operate, and owned by your team.
Working automation
A production-ready Claude workflow, Skill, or agent built around an actual business process—shaped to your voice and process, with agents that hand off to each other and compose into one flow instead of running as isolated toys.
Connected context
Approved data, tools, and systems connected through APIs and the Model Context Protocol—plus one governed place agents read from and write to, so context compounds and every new agent builds on what already exists.
Safe operating model
Guardrails, human-review points, permissions, and source-of-truth ownership designed into the workflow—plus monitoring and feedback loops that catch failures early and keep automation trustworthy as it scales.
Team ownership
Runbooks, documentation, and hands-on training so your team can operate, adjust, and build new agents with confidence—the workflow does not stay consultant-dependent.
Claude automation in the wild
We build with Claude, in public—here's one we shipped and open-sourced.
Claude AIAI AutomationIntegration Spine™
Ten Agents, One Backbone
We ran parts of our own company on ten connected Claude agents—one system, not ten demos.
- Connected Claude agents
- 10
- Shared governed backbone
- 1
- Workflows automated end-to-end
- 5+
dgtl Bytes & Perspectives
How we think about AI automation
Backed by real AI & automation credentials
Salesforce Agentforce Specialist · Purdue Generative AI · HubSpot Architecture · full-stack integration engineering—the expertise behind every build.
Explore all certifications
Post Graduate Program in AI and Machine Learning
Issued: Sep 2025
Credential ID: 161963791
Issuer: Purdue University
Demonstrates advanced training in Python-based data science, machine learning, and natural language processing, with hands-on experience applying AI models to real-world business and analytics use cases.
Verify Credential for Post Graduate Program in AI and Machine LearningGenerative AI for Business Transformation
Issued: Apr 2025
Credential ID: 141186682
Issuer: Purdue University
Demonstrates applied expertise in using generative AI across software, marketing, sales, and R&D to automate workflows, enhance decision-making, and drive scalable business innovation.
Verify Credential for Generative AI for Business Transformation
Salesforce Certified AI Associate
Issued: Nov 2024
Credential ID: 5247282
Issuer: Salesforce
Demonstrates expertise in designing, deploying, and managing Salesforce AI agents, including prompt engineering, data integration, and lifecycle management to drive intelligent, automated business workflows.
Verify Credential for Salesforce Certified AI AssociateSalesforce Certified Agentforce Specialist
Issued: Nov 2024
Credential ID: 5287501
Issuer: Salesforce
Demonstrates expertise in designing, deploying, and managing Salesforce AI agents, including prompt engineering, data integration, and lifecycle management to drive intelligent, automated business workflows.
Verify Credential for Salesforce Certified Agentforce SpecialistStart with one workflow.
Build the smallest useful version, wire it to the data it needs, then train your team to own it. That's how AI stops being a demo and starts compounding.
Discuss a Claude workflow
We build with Claude in public—see what we've shipped and open-sourced. See the work