GTM ai engineering

Putting marketing AI into production

Production-grade AI for the marketing and go-to-market workflows your team relies on—engineered by senior AI talent in your time zone and measured by GTM outcomes.

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We’ll explore your technology goals and challenges
You’ll get expert insights on the best path forward
We’ll outline next steps to bring your solution to life
BUSYWORK EATS THE DAY

Agents absorb the repetition, people keep the judgment

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Data orchestration

Stop losing time to disconnected data across your CRM, marketing platforms, and data warehouse. We unify customer information into one reliable view, giving GTM teams the context they need to launch more targeted campaigns, score leads accurately, support customer success and retention, and power dependable AI workflows.

A group of business professionals collaborating in a lush urban park with towering skyscrapers in the background, symbolizing innovation and efficiency. The scene represents machine learning models optimizing business operations, as technology and sustainability converge to enhance productivity and decision-making in a modern corporate environment.

Agentic workflow automation

Reclaim the hours your team loses to data entry, lead routing, scoring, campaign QA, and other repetitive tasks. We build AI agents and automated workflows that handle high-volume work while keeping your team in control through human-in-the-loop approvals. Marketing and sales teams spend less time managing data, and sales reps gain more time for work that drives revenue.

A group of business professionals collaborating in a lush urban park with towering skyscrapers in the background, symbolizing innovation and efficiency. The scene represents machine learning models optimizing business operations, as technology and sustainability converge to enhance productivity and decision-making in a modern corporate environment.

Pilot-to-production hardening

Turn your AI demo into a reliable, board-ready asset. We put the governance and scalable architecture in place to quickly move AI pilots into production, then continuously improve them against measurable marketing outcomes.

A group of business professionals collaborating in a lush urban park with towering skyscrapers in the background, symbolizing innovation and efficiency. The scene represents machine learning models optimizing business operations, as technology and sustainability converge to enhance productivity and decision-making in a modern corporate environment.

Signal-based outbound infrastructure

Reach prospective customers when they show intent—not weeks later. We build infrastructure that monitors real-time buying signals, including job postings, combines them with customer research from multiple data sources, and triggers personalized outreach. Every interaction is written back to your CRM.

We'll map your GTM workflows by volume, cost, and repetition.
You'll identify the high-impact quick wins with the fastest time-to-value.
We'll name the first one to build and what it's worth.
Case Studies

Our client impact in action

One question, one expert, booked in seconds

Lux Research's clients waited to reach the analysts who wrote the research: 75% of inquiries took more than seven days to schedule. FullStack built Luxer, an AI assistant that answers from Lux's own library with citations, maps the topic to the right expert, and books the meeting. Now 35% schedule within 48 hours.

A governed data layer under the marketing surface

A Fortune 500 hospitality leader's guest experience ran on a backend-for-frontend (BFF) layer with duplicated content and no data governance, leaving downstream AI nothing trustworthy to reason from. FullStack rearchitected it as a governed data access layer, migrating Hero Offers, Reserve Offers and Marketing Rooms, and built the pipelines now feeding retrainable models and guest-facing AI.

Agentic routing that escalates instead of guessing

A regulatory compliance provider needed call review at a scale humans couldn't reach. FullStack built an agentic system that sorts each sentence by issue type, routes it to the right model without a human prompt, and surfaces a ranked report. Reviewers went from 500 sentences per call to 5, at 93% accuracy—parity with human auditors.

testimonials

What our clients are saying

FullStack’s deep understanding of BenjaminWest’s needs, coupled with consistent updates, made the collaboration seamless and the outcome outstanding.
Joe Eikelberner, COO
BenjaminWest
FullStack acted as true partners and advisors. The expertise around AI and the level of developers, engineers—whatever role it was that came to the table—was just phenomenal.
Marisa Kopec, CEO
Lux Research
Speed is only the byproduct; the real value is better software and better use of our people.
Raj Tatta, VP of Engineering
Paciolan
FullStack turned our vision for The Launchpad into reality. Their intuitive design approach delivered an app that provides IT buyers a seamless and hassle-free experience, effortlessly connecting them with the ideal tech vendors.
Tonya Turrell, Founder & CEO
Technology Match
FullStack completely transformed our company's app, breathing new life into how we service our customer base. Their innovative and collaborative team delivered an application experience that we're proud to have in the market!
Jay Williams, Software Manager
Green Mountain Power
FullStack’s deep understanding of BenjaminWest’s needs, coupled with consistent updates, made the collaboration seamless and the outcome outstanding.
Joe Eikelberner, COO
BenjaminWest
FullStack acted as true partners and advisors. The expertise around AI and the level of developers, engineers—whatever role it was that came to the table—was just phenomenal.
Marisa Kopec, CEO
Lux Research
Speed is only the byproduct; the real value is better software and better use of our people.
Raj Tatta, VP of Engineering
Paciolan
FullStack turned our vision for The Launchpad into reality. Their intuitive design approach delivered an app that provides IT buyers a seamless and hassle-free experience, effortlessly connecting them with the ideal tech vendors.
Tonya Turrell, Founder & CEO
Technology Match
FullStack completely transformed our company's app, breathing new life into how we service our customer base. Their innovative and collaborative team delivered an application experience that we're proud to have in the market!
Jay Williams, Software Manager
Green Mountain Power
Due Diligence First

Find your high-impact GTM quick wins

Every engagement begins with an honest assessment of current workflows and use cases. We identify opportunities with the fastest time to value, diagnose technical and operational constraints, and establish the unified data foundations the work requires. Then, through a 90-day build-and-transfer, we build scalable revenue systems, validate the results, and train your team to own it.
A group of business professionals collaborating in a lush urban park with towering skyscrapers in the background, symbolizing innovation and efficiency. The scene represents machine learning models optimizing business operations, as technology and sustainability converge to enhance productivity and decision-making in a modern corporate environment.

A live workflow in 6–8 weeks*

We map sales and marketing processes in one to two weeks, then put one workflow into production using real cases.

A group of business professionals collaborating in a lush urban park with towering skyscrapers in the background, symbolizing innovation and efficiency. The scene represents machine learning models optimizing business operations, as technology and sustainability converge to enhance productivity and decision-making in a modern corporate environment.

Measured from a Week 0 baseline

Before anything changes, we document the workflow’s time and cost, along with its success metrics and leading indicators. That Week 0 baseline gives you credible evidence of improvement and a business case your CFO can evaluate.

A group of business professionals collaborating in a lush urban park with towering skyscrapers in the background, symbolizing innovation and efficiency. The scene represents machine learning models optimizing business operations, as technology and sustainability converge to enhance productivity and decision-making in a modern corporate environment.

We build the systems, not the campaigns

We're not an ad agency. We don’t offer media buying, creative, or campaign management. Unlike product marketing, which owns messaging, or RevOps, which maintains existing processes and data accuracy, we build what your marketing and revenue operations run on and hand it back to your team.

A group of business professionals collaborating in a lush urban park with towering skyscrapers in the background, symbolizing innovation and efficiency. The scene represents machine learning models optimizing business operations, as technology and sustainability converge to enhance productivity and decision-making in a modern corporate environment.

Not every workflow qualifies

Agent-ready work has sufficient volume and repetition, accessible data, and a limited need for subjective judgment. If a process doesn’t meet those criteria, the workflow assessment will identify why and recommend whether to refine, defer, or avoid automating it.

*These are typical time estimates and actual times may differ based on project complexity and scope.
COMPREHENSIVE SOLUTIONS

Explore FullStack's GTM engineering and AI engineering services

We are model- and vendor-agnostic. We work with the AI tools your team already uses and the platforms that support modern GTM systems, including Claude, ChatGPT, and Gemini for models; Clay, Apollo, and Bombora for buying signals; HubSpot and Salesforce as systems of record; and MCP, n8n, and Zapier for integration and orchestration.
  • Multi-step agent design and prompt engineering with bounded autonomy and approval gates
  • Identity resolution and field normalization across GTM systems
  • Automating processes like lead routing, scoring, qualification, and campaign QA
  • Evaluation harnesses and golden-dataset regression suites
  • Signal-driven enrichment and outreach with Clay plus custom services
  • CRM write-back and closed-loop attribution instrumentation
  • Warehouse and cloud AI foundations on Snowflake, Databricks, Vertex AI or Bedrock

Partner with FullStack and put marketing AI where it moves a number

Enterprise Partnerships

Turn siloed GTM data into board-ready, high-impact wins

For enterprise sales and marketing leaders managing complex, multi-system environments, we transform fragmented customer and campaign data across the CRM, MAP, CDP, and warehouse into a unified GTM asset. We engineer secure, compliant AI workflows designed to meet enterprise governance requirements and produce measurable business results you can take to the board.
Mid-Market Solutions

Launch high-impact AI-powered GTM with zero heavy lifting

For mid-market teams ready to adopt AI without diverting internal engineering resources, we remove the technical burden of getting started. In six to eight weeks, we can scope and launch a core marketing automation workflow, measure its results against a Week 0 baseline, and prepare your team to operate it.
This approach helps early-stage and SaaS companies prove ROI before adding headcount, making a GTM hire, or committing to a full-time GTM engineer. It’s especially useful for teams moving toward product-market fit that need speed without creating another disconnected system.
our blog

Featured articles

Focused student using agentic AI learning tools on a laptop in a modern classroom library, illustrating real-world agentic AI applications for personalized education and academic support.

5 Real-World Problems Agentic AI Is Solving Today

Discover how agentic AI problem solving transforms real-world industries with practical applications, intelligent agents, and proven AI use cases.
Read post

The Truth About Agentic AI: Common Misconceptions Debunked

Agentic AI is rising fast—but is it misunderstood? Explore agentic AI misconceptions, risks, and how this tech really works for modern businesses.
Read post
Brian Niccol speaks onstage in a dark blazer and open-collar shirt during a Starbucks investor day presentation, gesturing with both hands in front of a large screen that reads ‘Back to Starbucks’ over a photo of a busy café interior.

Inside Starbucks’ AI Inventory Collapse and How FDEs Could Have Saved It

Starbucks scrapped its AI inventory tool after just nine months. This article examines what failed and how forward-deployed engineers could have prevented it.
Read post

Frequently Asked Questions

What is the GTM engineer role in AI engineering?
GTM AI engineering is the software engineering work required to put AI into production across marketing, sales, and go-to-market workflows. A GTM engineer connects business processes with technical execution through API integrations, data modeling, SQL or Python development, workflow automation, and multi-step AI agents with bounded autonomy and approval gates.
The role differs from product marketing, which owns messaging, positioning, and competitive differentiation. GTM engineer salary benchmarks vary widely by source, experience level, and methodology, but the role can be expensive and difficult to hire for. As a result, many teams partner with an external engineering firm to validate the opportunity before adding a full-time position.
How does FullStack automate lead routing and scoring?
FullStack builds marketing automation systems for lead routing, scoring, qualification, and campaign QA, with human-in-the-loop approvals where judgment is required. Predictive lead scoring can use a unified view of CRM and warehouse data, while enriched routing can bring in sales engineers when a lead requires technical qualification.
The goal is to improve speed and sales efficiency without sacrificing control. At Lux Research, 35% of inquiries are now scheduled within 48 hours, while FullStack’s agentic routing system for a compliance provider achieved 93% average accuracy, matching human-auditor performance.
What data work comes before the AI agents?
AI agents are only as reliable as the data and business context beneath them. FullStack begins with the necessary data pipelines and infrastructure, including a permission-aware layer across your CRM, marketing automation platform, customer data platform, and warehouse.
That work can include data modeling, identity resolution, field normalization, role-based access control, data governance, and action-level audit logging. Together, these capabilities create a clean, unified data foundation for reliable AI workflows.
How does signal-based outbound work?
FullStack builds infrastructure that monitors real-time buying signals as part of a broader go-to-market motion. The system can enrich account and contact data using Clay and custom services, trigger personalized outreach based on defined rules, and write each interaction back to the CRM.
These workflows can also support account-based marketing programs focused on high-value accounts. The result is a consistent, responsive sales process that reduces manual research without creating disconnected outreach activity.
Does FullStack set GTM strategy, and do we need a technical specialist in-house?
FullStack engineers the revenue systems that support your go-to-market strategy, sales operations, marketing operations, and broader revenue teams. We don’t replace creative problem-solving or campaign ownership, and we do not provide media buying, creative services, or campaign management.
Workflow mapping identifies the first system to build and defines its success metrics. Through the build-and-transfer model, FullStack also trains your team to operate and improve the system, so you do not need an in-house technical specialist or a dedicated engineering team to get started. The focus is scalable execution: integrating new tools into a coherent GTM system rather than adding more disconnected workflows.
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