AI Agent Builders by GammaDX

The right stack for the job, not a preferred-vendor shortlist.

We work across leading models, enterprise platforms and data infrastructure. The final architecture follows your systems, security boundary, operating constraints and the job the agent must do.

Technology names indicate platforms we can design around and integrate with. They do not imply vendor endorsement, certification or partnership.

Model choice is an architecture decision.

We select and evaluate models against the workflow: quality, latency, cost, data handling, tool use and deployment constraints.

Anthropic Claude

Reasoning, analysis and tool-using agents with strong instruction-following.

MODEL PROVIDER

Google Gemini

Multimodal agents across text, image, audio and large-context workloads.

MODEL PROVIDER

OpenAI

General-purpose reasoning, structured output and multimodal agent workflows.

MODEL PROVIDER

xAI Grok

Reasoning and real-time information workflows using the Grok model family.

MODEL PROVIDER

01 / Build layer

Agent orchestration

The frameworks and engineering patterns that turn a model into a bounded, observable workflow.

LangGraph

Stateful workflows, durable execution and human review points.

CrewAI

Role-based multi-agent coordination for defined operational tasks.

Microsoft Semantic Kernel

Enterprise agent orchestration across .NET, Python and Java.

Pydantic AI

Type-safe Python agents with explicit validation and dependencies.

Model Context Protocol

A standard interface for exposing tools and context to agents.

02 / Experience layer

Content, marketing and digital experience

Platforms where agents can plan, prepare, validate and route customer-facing work.

MarkAI/Opal by Optimizely logo

MarkAI/Opal by Optimizely

AI agent orchestration for marketing and digital experience workflows across Optimizely.

Adobe Experience Cloud

Content, campaign, analytics and personalisation operations.

Sitecore

Content, experience and personalisation workflows.

Contentful

Structured content operations for composable digital experiences.

HubSpot

Marketing, sales and service workflows within the HubSpot platform.

03 / Operational layer

CRM, service and workflow systems

Systems of record and work queues that agents can read from and act within under controlled permissions.

Salesforce

CRM, service, sales and Agentforce-connected workflows.

Microsoft Dynamics 365

CRM and business operations across the Microsoft stack.

ServiceNow logo

ServiceNow

IT, employee and customer service workflow automation.

Microsoft 365

Email, documents, collaboration and organisational knowledge.

Atlassian

Jira and Confluence workflows for delivery and knowledge operations.

04 / Data layer

Cloud, data and retrieval

Production infrastructure for model access, governed data, retrieval and durable agent state.

Microsoft Azure

Enterprise hosting, identity, model access and AI operations.

AWS

Cloud infrastructure and managed foundation models through Bedrock.

Google Cloud

Cloud infrastructure, data services and Vertex AI.

Databricks

Lakehouse data and Mosaic AI for governed enterprise workloads.

Snowflake

Enterprise data and Cortex AI within the Snowflake platform.

MongoDB

Operational document data and vector search for retrieval.

PostgreSQL

Durable relational data and pgvector-based semantic retrieval.

05 / Control layer

Evaluation, observability and delivery

Tools that make agent behaviour testable, traceable and maintainable after launch.

LangSmith

Tracing, evaluation and monitoring for agent workflows.

Arize Phoenix logo

Arize Phoenix

Open-source tracing and evaluation for LLM applications.

Weights & Biases

Experiment tracking, evaluation and model operations.

Guardrails AI logo

Guardrails AI

Structured validation and safeguards around model outputs.

GitHub

Version control, delivery automation and governed change history.

Your stack remains yours.

We prefer supported interfaces, narrow permissions and components your team can operate. Where a simpler workflow or existing platform is the better answer, we say so.

Bring the systems you already run.

We will map the job, identify the cleanest connection points and recommend a stack your team can govern after handover.

01Which job, done by whom, how often
02Which systems it touches and who owns them
03What must never happen without a human
04How you would know it is working