Climaty.ai VS Codegres.org

Climaty.ai's answer

• Stellantis
• Wpp
• Omnicom Media Group

Climaty.ai's answer

When we started building Climaty AI, we saw a fundamental problem in how marketing operates. Businesses have access to more data, platforms, and technology than ever before, yet teams still spend an enormous amount of time connecting systems, interpreting insights, and manually executing decisions.

We believed AI could do much more than simply generate content or provide recommendations. It should be able to understand context, make intelligent decisions, and turn those decisions into action.

That's the thinking behind Climaty AI.

We've built an enterprise Agentic AI platform where specialised AI agents work together across the marketing ecosystem, bringing planning, intelligence, execution, and optimisation into one connected environment.

What makes our approach different is the combination of multi-agent intelligence, real-time data, enterprise context, and the ability to execute directly across marketing platforms, while keeping people in control of important decisions.

For us, the goal has never been to replace marketers. It's to remove the operational complexity that holds them back, giving teams more time to focus on strategy, creativity, and growth.

We believe the future of marketing isn't about adding more tools. It's about making the entire marketing ecosystem work intelligently together. And that's exactly what we're building at Climaty AI.

Climaty.ai's answer

Most marketing teams already have access to powerful platforms. The challenge is getting them to work together without spending hours on manual processes, switching between tools, and making decisions with incomplete information.

That's the problem we built Climaty AI to solve.

Our approach is different because we focus on what happens after the insight. It's not enough to tell a marketer what needs to improve. We want to help them actually get it done.

For example, a team can turn a simple brief into a structured campaign plan, using historical account data, audience intelligence, and live platform benchmarks. Our agents can also identify performance gaps, recommend optimisations, and support execution across connected platforms.

And importantly, the marketer remains in control, with visibility into recommendations and approval over what goes live.

For us, the real value isn't in how many tasks AI can perform. It's in how much time we can give back to marketing teams, how much complexity we can remove, and how much better we can help them perform.

That's what we're focused on at Climaty AI: building technology that solves real marketing challenges rather than adding another tool to an already crowded stack.

Climaty.ai's answer

At Climaty AI, we're building for marketing teams that are managing increasingly complex operations while being expected to deliver faster, more measurable results.

Our primary audience includes enterprise brands, marketing agencies, and growth-focused businesses, particularly CMOs, marketing directors, heads of digital and performance marketing, growth leaders, and marketing operations teams.

These are professionals managing multiple platforms, large campaign portfolios, significant media investments, and growing volumes of data. Their biggest challenge isn't access to technology. It's the time and effort required to connect insights, coordinate teams, execute campaigns, and continuously improve performance.

We also work towards empowering the people managing these operations every day, from media planners and campaign managers to performance specialists and digital strategists.

Our focus is on organisations that want to move beyond fragmented tools and manual processes, using Agentic AI to make marketing operations more efficient, decisions more informed, and execution more effective.

Ultimately, we're building Climaty AI for marketers who want to spend less time managing the process and more time driving business growth.

Climaty.ai's answer

The idea behind Climaty AI came from something we kept noticing in the marketing industry.

Over the years, marketing technology has evolved tremendously. We have better platforms, more data, and more sophisticated tools than ever before. But when you look at how marketing teams actually operate, so much of the work is still manual.

Teams are constantly switching between platforms, pulling reports, connecting data, building campaigns, and figuring out what to optimise next.

And we kept asking ourselves, with all this technology available, why does marketing still have to be so complicated?

That's really where Climaty AI began.

We wanted to build something that went beyond another dashboard or a tool that simply gave recommendations. Our idea was to create a platform where specialised AI agents could work together, understand what a marketer is trying to achieve, and help take that objective all the way from planning to execution and optimisation.

And importantly, we wanted marketers to remain in control throughout that process.

What started as an ambitious idea has grown into something we're incredibly proud of. In a relatively short time, we've built a platform, earned the trust of brands, and received recognition from the industry.

Of course, those milestones mean a lot to us. But what excites me even more is knowing that we're addressing challenges marketers have been dealing with for years.

For me, Climaty AI isn't just about bringing AI into marketing. It's about changing how marketing gets done.

And we believe we're only beginning to explore what's possible.

Climaty.ai's answer

At Climaty AI, we've built our platform on a multi-model, multi-agent architecture, combining multiple Large Language Models (LLMs) with our own Small Language Model (SLM).

Rather than depending on a single foundation model, we use different models based on the requirements of specific tasks. Larger language models support complex reasoning, natural language understanding, and decision-making, while our own SLM forms part of the architecture for more focused, task-specific processing.

Our technology also incorporates multi-agent orchestration, persistent enterprise context, real-time data processing, and API-level integrations. These components allow specialised agents to coordinate workflows, interpret marketing requirements, analyse performance data, and support execution across connected platforms.

Human oversight is built into the system, allowing users to review recommendations, understand decisions, and approve critical actions before execution.

Our approach is to combine the strengths of different language models with specialised agents and direct platform integrations, creating an Agentic AI system designed specifically for real-world marketing operations.