The harder decisions begin once AI moves beyond experimentation.
What use cases justify investment? Is the data ready? Should we use an existing model, customize one or build something more specialized? How will it integrate with the applications and workflow our teams already use? And once deployed, how will we manage accuracy, security, cost and performance?
Infojini provides AI development services including strategy, architecture, engineering, integration, deployment and optimization. We help you discover real use cases, avoid unnecessary complexity and overhead and engineer the data, applications, cloud infrastructure and operational environment needed to make AI work in production.
From strategy, GenAI, and AI agents to machine learning, integration, and MLOps, we build AI around your data, existing systems, security requirements, and the realities of production at scale.
Identify high-value AI use cases before committing engineering resources. We assess data readiness, feasibility, integration needs, risk, adoption, and the roadmap to move forward.
Create custom GenAI solutions around your proprietary data. We engineer RAG architectures, knowledge apps, enterprise copilots, and contextual tools with strict hallucination controls.
Adapt and deploy models tailored to your business logic. We specialize in domain-specific SLMs, LoRA/QLoRA fine-tuning, model distillation, private hosting, and cost-efficient routing.
Create AI agents to fetch context, call APIs, and run multi-step workflows. We bake orchestration, permissions, human approval, observability, and auditability into the agent architecture.
Create AI-native products or extend your current applications with AI capabilities. We combine AI engineering with web, SaaS, API, backend and workflow programming.
Connect AI to CRMs, ERPs, data platforms, APIs, cloud environments & enterprise apps. Give AI the context and system access it needs to support decisions and approved actions.
We build AI around real business problems, with the data, integrations, controls, and architecture needed to perform reliably at scale.
We can assess the data, architecture, integrations, model options, risks, and production requirements to give you custom AI development solutions.
Our approach gives AI initiatives enough structure to reduce risk without slowing execution, while adapting to the data, systems, constraints, and business outcomes each use case requires.
Start with the business problem, workflow, users, data, systems, constraints, and expected outcome. Use cases are assessed for feasibility and value before engineering begins.
Define the technical path across model selection, architecture, data, cloud, security, governance, integrations, evaluation, and rollout priorities.
Develop the models, agents, applications, APIs, pipelines, and interfaces required for the solution. PoCs or MVPs can validate feasibility before larger investment.
Connect AI with enterprise applications, databases, APIs, knowledge sources, cloud platforms, and workflow tools, with permissions, approvals, logging, and controls built in.
Strengthen performance, monitoring, governance, deployment, cost efficiency, drift management, and integrations to support wider production use.
See how Infojini applies AI engineering expertise to real operational challenges, from workflow automation and decision support to customer experience and new digital products.
Peak sales pushed support volume to 25,000 monthly tickets and response times past 14 hours. We built AI-powered support automation with RAG, live order lookup, and human-assisted escalation.
OpenAI GPT-4o
LangChain + LangGraph
Pinecone
A rapidly growing FinTech lending company in the USA offering digital personal and small business loans.
Azure Document Intelligence
OpenAI GPT-4o
LangChain + LangGraph
As an AI development agency, Infojini combines AI engineering with industry expertise to build systems that fit the workflows, risks, regulations, and operating realities that define your industry.
We select the models, frameworks, cloud platforms, and tools that best fit your architecture, data, security, scale, performance, and cost requirements.
Let’s identify the right stack, the right starting point, and the right level of investment for your next AI initiative.
One delivery partner across the technologies, systems, and operational requirements that production AI depends on.
Explore Why Infojini
"We've worked with several artificial intelligence consulting companies before, but this team actually delivered production ML models in 90 days—not just another strategy deck."
"The machine learning consulting team helped us automate clinical document classification and streamline workflows across departments. What impressed us most was their focus on measurable outcomes, not just technology recommendations."
"Their AI and ML consulting expertise helped us improve predictive maintenance across our operations. The solution helped our teams identify equipment risks earlier, reduce unplanned downtime, and make maintenance decisions faster."
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Our AI experts can help you assess the use case, identify the technical dependencies, and map the right path across data, architecture, integration, and deployment.
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