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Lattice Partners is a key player in the agentic implementation space, specifically for the enterprise market. They are active proponents of the OpenClaw framework, an open-source tool that allows for the creation of model-agnostic AI agents. By championing such frameworks, they are pushing the ecosystem toward production standards where agents are expected to be reliable, integrated into existing business systems (like CRMs), and capable of switching between different LLMs depending on the task.
In the broader agent stack, Lattice sits at the implementation and orchestration layer. They matter to the ecosystem because they provide the bridge between foundation models (Anthropic, OpenAI) and real-world business utility. Their focus on "agentic work" rather than simple chat suggests a commitment to autonomous systems that can handle long contexts and follow complex instructions. For builders, Lattice serves as a case study in how to productize agents for non-technical industries like manufacturing and healthcare.
Lattice Partners is an AI transformation firm that addresses the gap between corporate AI interest and actual production deployment. Founded by alumni from McKinsey, Boston Consulting Group, and Google, the company is built on the premise that enterprise AI requires more than just high-level strategy. They operate as a plug-in AI team for organizations in regulated or data-heavy sectors, including healthcare, finance, and manufacturing. Unlike traditional consultancies that deliver slide decks, Lattice builds custom software, installs agents into existing workflows, and provides the direct technical training required to make those tools stick.
A central part of their work is the development and deployment of AI agents. The firm advocates for moving beyond simple terminal or web chat interfaces toward agents that live where work happens—integrated into CRMs like Salesforce, connected to internal data pipelines, or surfacing in custom dashboards. They are active proponents of the OpenClaw framework, an open-source tool designed for building autonomous agents. Their technical approach is model-agnostic; while they frequently use Anthropic’s Claude models for reasoning tasks, they design architectures that allow clients to swap providers (OpenAI, Google, or local models via Ollama) without rebuilding the underlying logic. This flexibility is a deliberate hedge against the rapid shifts in model pricing and performance.
The founders, Christian Yeghnazar and Colin McDonnell, bring a background in traditional management consulting to the technical realities of LLM development. This pedigree is reflected in their three-step process: Discover, Design, and Deploy. In the Discover phase, they audit current tools and workflows to identify specific ROI opportunities—like reducing research time or automating document processing. The Design phase involves scoping the technical architecture and defining success metrics. Finally, the Deploy phase includes building the solution, integrating it with the client's stack, and monitoring performance. This methodology is designed to provide the rigor of a large consulting firm with the speed of a software startup.
Lattice Partners works with a diverse range of clients, from investment firms like Clocktower Group to media companies like Omaha Productions. Their reported outcomes include an 80% reduction in research time for some clients and significant annual cost savings through automation. By focusing on specific industries like legal and retail, they address narrow but high-value problems such as automated internal knowledge bases and sales pipeline automation. Their work with Clocktower Ventures, for instance, involved training the entire organization to use tools like Claude and ChatGPT effectively, shifting the firm's daily operations toward an AI-first model. This combination of software building and organizational change management is their primary differentiator in an increasingly crowded consulting market.
An open-source AI agent framework implementation for production environments.
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