If you are considering developing your own AI agents, there are two drawbacks you will need to consider: the research and development budget, and time.
Most businesses can benefit from automation. Today, AI agents can automate a significant percentage of the work employees do, as long as there is high-quality data and a well documented process in place. Most tasks performed on a computer or phone can also be automated to some degree, and this scope is still growing.
A major challenge arises at the implementation stage. Large Language Models (LLMs) are the brains behind this technology, and have already shown incredible reasoning potential. But even so, we need to add multiple layers of tools, evaluations, security and integrations, as well as exposure to process automation consulting to translate business problems into AI logic.
Two Schools of Thought
Larger organizations are going the route of incorporating their own data and AI teams. However, building with engineers often requires longer development cycles and higher costs, and internal momentum can work against agility.
Other organizations rely on tech firms like Morphal, with the expertise and technology to achieve similar results, plus a strong focus on data security and compliance.
What Morphal Does
We have built our own agent infrastructure that integrates with most business technology standards, so that our clients do not require developers, data scientists, or specialized technical staff. Our agents have everything they need to work behind the scenes and solve your existing problems. So your team can keep focusing on higher-value work.
In addition, Morphal's agents can do something surprising: take on tasks humans have never touched before. Not because leaders didn’t want to, but because the labor involved was too slow, too expensive or too large to handle.
For example, you can now analyze every historical interaction with past clients before creating new technical proposals, a process that can be repeated for every new bid. This capability extends to software, operations, and any department previously limited by a lack of time or specialized talent.
