How the best AI development companies in Sri Lanka are transforming the future of enterprise AI

When mentioning enterprise AI, the first things that often come to mind for most are LLMs, chatbots and the occasional forecasting abilities brought on by custom solutions. However, numerous leading offshore software development companies in Sri Lanka will tell you that there’s more to enterprise AI than prompt-based tools and automatic recommendations.

There are multiple reasons for this. For one, the ever-evolving landscape of AI and its subset technologies keeps redefining benchmarks, keeping both organisations and software companies in Sri Lanka on their toes. The other reason is one that is universally well known, and evergreen – changing customer demands and preferences.

As customers continue to be spoilt for choice in markets that are increasingly saturated with options, businesses are under more pressure than before to either be relevant for their prospects, or face losing out to the competition. It is at this juncture that companies are questioning how to resonate with customers, and fast.

Cue AI and its various subset technologies, with the numerous ways these can be customised to suit any use case across any industry. Which is why in this article, we discuss three business areas where AI is commonly applied. We’ve also included a mini-guide to direct businesses on how to start their first AI project, or expand on an existing one.

Enterprise AI and CX

Chatbots are common constituents across most front-facing enterprise touchpoints, but resorting to a chatbot alone isn’t going to suffice in this day and age of automation. As customer volumes increase, so does the likelihood of inquiries that can benefit with instant escalation.

This is where AI agents come handy. Trained with historical data and powered by machine learning, AI agents work behind the scenes by setting appointments, sharing information and even making intelligent suggestions to cross-sell/up-sell products and services.

CX isn’t confined to chatbots and AI agents, though. Being an ecosystem of various tools and technologies, AI can be infused into any of the below CX components as well:

Customer Data Platforms (CDPs): A centralised profile of each customer that is pumped with data from various channels. Pattern recognition and forecasting via AI can be executed here.
Conversation intelligence and sentiment analysis: These tools are a treasure trove of data, which can be used to identify customer moods and determine preferences based on language and tonality used during communication.
Digital Experience Management (DXM): AI-powered analytics from CDPs and conversation intelligence tools can offer leverage to DXM solutions, by automatically creating relevant customer journeys depending on various parameters.
Sales enablement: Although not a CX tool per se, sales enablement solutions stand to significantly benefit via AI-powered CX analytics, as sales teams now have insight on where their customers lean sentimentally. These analytics can also determine training modules administered via the sales enablement solution, to deliver lessons for sales agents that best align with addressing customer pain points.

Enterprise AI data engineering

Many organisations are sitting on big data that’s raw and unfiltered. This can pave the way for AI-powered data analytics, which involves training models to identify trends within this data.

Intelligent recommendations can follow at a close second, either by guiding leadership teams, or autonomously executing tasks. With LLMs now proficient in understanding context and intent behind language, the best software companies in Sri Lanka build with cyber security and compliance in mind – both of which require vast amounts of training data in order to build solutions that are more predictive by nature.

AI-powered enterprise workflow automation

Industries that deal with the constant inflow and outflow of raw materials and other goods (such as manufacturing and logistics) both require actions taken in a timely manner to keep the supply chain flowing smoothly. Highly regulated industries such as healthcare and financial services are more in need of meeting compliance requirements, which means tasks need to be fulfilled on time in order to avoid warnings and fines.

Workflow automation is highly beneficial for such use cases, and adding to that, AI-powered workflow automation can meet more criteria than simply checking an item off a list. The best IT company in Sri Lanka knows this; many leading technology outsourcing companies in the island now don’t deliver custom software and applications, unless it has an AI-powered workflow automation component integrated to it.

How to create and manage AI projects with AI development companies in Sri Lanka

With much buzz surrounding the implementation of custom AI for enterprise use, it is advisable to first do your due diligence before diving deep into development. This how-to guide is applicable to both brand new AI projects as well as existing ones; simply adapt these steps for where your team is headed in its AI development.

Whether you are partnered with the best offshore software company in Sri Lanka or elsewhere, what truly matters is whether your agency partner is there with you at all times, being in lockstep with you to execute the below steps for creating and managing your own AI project.

Conduct a detailed assessment of your needs

Before you embark on any kind of development, it is imperative to conduct a thorough assessment of your current business situation, its needs and its pain points. For this, gather relevant team members to break the ice around topics such as:

Customer complaints,
Resource under or overutilisation,
Employee bottlenecks,
Silos in data or workflows,
Any KPIs that are failing to be met.

Feedback gathered from this assessment can then be collated into a brief. This shall then serve as a primary point of reference for your AI development partner, so that their teams can get a better understanding before proposing relevant solutions, technologies and timelines.

Start small, ideally with a beta version or MVP

Any technology-based project is susceptible to errors during its infancy. This is even more so for AI projects, especially as model training can reveal numerous errors during initial releases – which will require further fine tuning before a workable version can be launched.

In this case, it is always wise to start with a beta version of your final product, or a Minimum Viable Product (MVP). While a beta is forthcoming about the fact that errors may exist, an MVP only consists of the most essential features that have been tested for optimal functionality.

For AI projects in particular though, it is also highly recommended to ensure your existing systems are in order and available as a failover, so day-to-day operations can continue. Either this, or have a non-AI (but reliable) system to serve you in the interim – only because the initial phase of trial and error is bound to be longer and perhaps even more tedious than your teams may have anticipated.

Monitor KPIs, and adjust to scale

While many KPIs may have already been ascertained during the assessment stage, it is likely that many more which require monitoring may only come under the attention of your team, much later. In this case, remain Agile, and tweak your dashboards to incorporate new KPIs for a holistic analysis of your AI-powered solution(s).

Scaling is also applicable to cloud-based infrastructure and other resources. As the project progresses and usage fluctuates following release, your AI development partner needs to be at the forefront of orchestrating which resources to utilise and which pricing models to use, in order to remain cost-efficient.

Many software development companies in Sri Lanka, have partnerships with most global cloud service providers. This ensures that they can adjust and optimise on behalf of their clientele, in accordance to their budget.

In conclusion…

Enterprise AI has come a long way since its early days of simply using a prompt-based genAI tool for seeking answers. Now, leading AI development companies in Sri Lanka deliver bespoke solutions, depending on the goals and constraints their clients have. This includes building solutions even for niche requirements, irrespective of industry or company size.

In particular, enterprise AI dominates the below business areas:

Customer Experience (CX): By infusing AI into most CX components (such as CDPs and sentiment analysis tools), teams are able to get a deeper understanding of what customers are thinking, and where their preferences lie.
Data engineering and analytics: Puts otherwise inert big data to use by training models with the same, to deliver accurate forecasts and recommendations.
Workflow automation: Intelligently automates long, intricate processes to ensure business continuity, compliance and even cyber security.

However, before venturing into developing any AI-powered solution, a comprehensive business assessment is needed. This needs to then be combined with beta versions during the initial stage – before a complete and reliable version can be launched.