Service Overviews

AI Development
Whether you’re building an AI-powered product from scratch or adding intelligence to an existing platform, we help you design and develop real, functioning AI tools. That could mean natural language processing, predictive models, AI-powered search, recommendation systems, or fully integrated workflows. Every build starts with feasibility, not fantasy—and ends with something that actually works.

LLM Fine-Tuning
Large Language Models are powerful—but generic. We fine-tune open-source or proprietary LLMs on your data, so they align with your voice, your expertise, and your domain. Whether it’s legal, medical, financial, or highly niche, we help you turn general-purpose models into specialized assets.

Prompt Engineering
The quality of an AI output depends on how you speak to it. We design prompt strategies that are consistent, context-aware, safe, and multilingual. From chat experiences to backend AI workflows, we make your interactions smarter by teaching your AI how to understand your intent.

RAG Solutions (Retrieval-Augmented Generation)
When you need accurate, up-to-date, and grounded responses, LLMs need help. RAG systems connect your models to real-time or private datasets. We build RAG pipelines that feed LLMs the right data—so your answers are fact-based, context-aware, and specific to your environment.

AI Agent Development
AI agents go beyond passive tools—they act. We build agents that carry out multi-step workflows, talk to APIs, make decisions, and interact with users. From copilots to internal assistants to chatbot layers, our agents are built to reason and respond within real systems.

AI Memory Solutions
We create systems where context isn’t lost. From personalized user experiences to persistent conversation logic, we build memory frameworks that let your AI remember past interactions, reference them meaningfully, and evolve over time—without losing coherence or safety.

Vector Database Integration
We implement vector storage systems like Pinecone, Weaviate, and FAISS to enable semantic search, intelligent recommendation engines, or advanced RAG infrastructure. This is where AI starts to understand meaning, not just keywords. We make that functionality real—and fast.

AutoML Integrations
AutoML platforms allow businesses to create ML models without building them from scratch. We help you use Google AutoML, Azure ML, or open-source tools to train, test, and deploy models faster—ideal for internal teams, fast prototyping, or non-expert AI environments.

MLOps Solutions
We turn ML models into stable, production-ready assets. That means versioning, deployment pipelines, performance monitoring, retraining, rollback, and scaling. MLOps is the infrastructure that keeps your AI running—and evolving. We build it so your models don’t just exist, they improve.

Why Sayogari

Because AI is only as good as the team behind it.

At Sayogari, we’ve been building AI systems before ChatGPT went viral. We understand what works—and what doesn’t. We know where to use LLMs and where not to. We don’t push AI where it doesn’t belong. And when it does belong, we make sure it performs.

We don’t just advise—we build. That means our strategies are grounded in execution. We know what tools are mature, what frameworks are stable, what models are safe, and how to integrate AI into systems with real users and real data.

Our clients trust us because we don’t oversell. We ask the hard questions: Is this viable? Will it scale? Is it ethical? Does it actually help?

We’re fluent in the language of founders, product managers, CTOs, and non-technical decision makers. We explain clearly, build efficiently, and deliver systems that aren’t just impressive—they’re useful.

And because we’re not locked into any one AI vendor or platform, our solutions are always tailored to your needs, not a service partner’s sales goals.

In One Year…

Your AI features aren’t experiments anymore—they’re assets.

Your users are benefiting from smarter interfaces. Your internal tools are running faster, with less overhead. Your support system is partially automated but fully coherent. Your recommendation engine is improving retention. Your workflows are enhanced by agents. Your search is semantic. Your onboarding is personalized. And your data systems are feeding intelligence instead of just collecting noise.

Your AI systems are monitored, retrained, and scalable. They aren’t a black box—they’re an understood, operational part of your business. You’re not constantly troubleshooting or backtracking. You’re iterating, expanding, improving.

And your competitors? They’re asking how you got so far ahead. You’ll know exactly how—and who helped.