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SoltoPro
AI & Innovation

We’ve been building with AI since before the hype.

Production systems with LLMs, RAG, and agents — from early research frameworks to enterprise deployments. We’ve watched three hype cycles come and go. We’re still shipping.

Capabilities

What we build with AI.

Eight capability areas. All delivered by senior engineers who’ve shipped these systems to production before.

Large Language Models (LLMs)

Architecture selection, fine-tuning, evaluation, deployment, and governance across all major providers.

Retrieval-Augmented Generation (RAG)

Custom knowledge pipelines that ground AI responses in your proprietary data. Accurate, auditable, hallucination-aware.

AI Agents & Orchestration

Autonomous agents that plan, use tools, and complete multi-step tasks. LangGraph, AutoGen, Semantic Kernel, custom frameworks.

Prompt Engineering

Systematic prompt design, evaluation frameworks, meta-prompting, chain-of-thought, and structured outputs.

AI Security & Governance

Threat modeling for AI systems, prompt injection defense, data leakage prevention, model governance, responsible AI policy.

Enterprise AI Integration

Connect AI to your existing systems — CRMs, ERPs, databases, APIs. Production-grade pipelines, not demos.

AI for Healthcare

HIPAA-compliant AI deployment, PHI-aware pipelines, clinical workflow automation, and compliance documentation.

AI Strategy & Roadmapping

Where to start, what to build, which models to use, how to measure ROI. Clear plans — no buzzwords.

Platform expertise

Every major AI stack. In production.

We evaluate, architect, and deploy across the full AI landscape — commercial and open source.

Microsoft AI

  • Azure OpenAI Service
  • Azure AI Studio
  • Microsoft Copilot
  • Copilot Studio
  • Semantic Kernel
  • Phi-3 / Phi-4
  • Azure AI Search
  • Prompt Flow

Google AI

  • Vertex AI
  • Gemini (Flash, Pro, Ultra)
  • Google AI Studio
  • NotebookLM
  • Gemma
  • Agent Builder

Anthropic

  • Claude 3.7 Sonnet
  • Claude Opus
  • Claude Haiku
  • Constitutional AI
  • Tool use & extended thinking
  • Claude API
  • Model Context Protocol (MCP)

Meta & Open Source

  • Llama 3.x
  • Mistral
  • Mixtral
  • Ollama / LM Studio
  • Open-weight fine-tuning

xAI & Frontier

  • Grok
  • Emerging frontier models
  • Multi-model evaluation & benchmarking

Frameworks & Tooling

  • LangChain
  • LlamaIndex
  • LangGraph
  • AutoGen
  • Haystack
  • ChromaDB
  • Pinecone
  • Weaviate
  • HuggingFace
  • FAISS
  • Weights & Biases
  • MLflow
Note: We don’t hold reseller partnerships that bias our recommendations. We pick the model that fits the use case — on latency, cost, accuracy, and governance.
Philosophy

How we think about AI.

Three principles we don’t compromise on.

01

Production or Nothing

95% of enterprise AI initiatives deliver no measurable return. We build for deployment — not demos. Every engagement ends with something running in production.

02

Security First, Always

AI systems are attack surfaces. We design with prompt injection defense, data isolation, output validation, and governance from the first line of code.

03

Right Tool, Right Problem

We’re not married to any vendor. We evaluate models on your specific use case, your data, your latency requirements, and your budget — then recommend accordingly.

AI engagements

Have an AI problem worth solving?

We’ll assess feasibility, recommend an architecture, and tell you what’s realistic — before you spend a dollar on infrastructure.