AI & Machine Learning

Generative AI Solutions

From strategy to production—RAG, AI agents, and LLM apps built with security, evaluation, and cost control in mind.

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Generative AI Solutions that turn your data into a competitive advantage. InnovariaTech delivers end‑to‑end generative AI development services—from strategy and prototyping to production rollout—so you can launch reliable, secure, and cost‑controlled AI experiences.

RAG knowledge bases for internal search and customer support

AI agents that execute workflows (tickets, reporting, onboarding, ops)

LLM apps and copilots for sales, finance, HR, and product teams

What We Build with Generative AI

We design and ship production-ready experiences—not just demos. Whether you need a customer-facing assistant or an internal copilot, we build systems that are measurable, maintainable, and secure.

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RAG-powered assistants

Answer questions using your docs, policies, tickets, and knowledge base

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Custom AI chatbot development

For websites, mobile apps, and support platforms

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AI agent development

Automating multi-step tasks (approve, verify, summarize, update systems)

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LLM development

Domain-specific reasoning, drafting, and structured output (JSON/SQL/actions)

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AI copilot development

Embeds directly into your product UI and internal dashboards

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Evaluation harnesses

Quality, safety, latency, cost monitoring + dashboards

Use Cases by Industry

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Customer Support

Deflect tickets with RAG answers, escalate complex issues with summaries, and maintain brand tone across channels.

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Sales Enablement

Auto-generate tailored outreach, proposals, and meeting briefs from CRM + product docs.

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Operations & Back Office

Agents that prepare reports, validate documents, and trigger workflows across tools.

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Compliance & Risk

Policy Q&A with citations, PII redaction, and audit-friendly logging.

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Product & Engineering

Copilots for triage, release notes, test case generation, and doc automation.

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Marketing & Content

Generate campaign copy, social posts, SEO content, and personalized messaging at scale.

Our Build Approach

Most GenAI projects fail because they skip the basics: data readiness, evaluation, security, and cost controls. Our approach makes generative AI measurable from day one.

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Discovery & GenAI consulting

We map use cases to business KPIs, define guardrails, and select the right architecture (RAG, fine-tuning, agents).

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Prototype (1–3 weeks)

We build a working MVP with a small dataset and an evaluation loop so you can see quality early.

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Production build

We harden the solution with observability, caching, retries, prompt injection defenses, and access controls.

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Launch & MLOps

We deploy in your preferred cloud, set up monitoring (quality, cost, latency), and iterate using real user feedback.

Technology Stack We Commonly Use

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Models

OpenAI, Anthropic, Llama-family, Mistral (selected based on cost, latency, privacy, and quality)

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Orchestration

LangChain, LlamaIndex, custom pipelines

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Vector DB / Search

Pinecone, Weaviate, Elasticsearch, Postgres + pgvector

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Hosting

Azure, AWS, GCP (including data residency considerations for EU/Gulf)

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App layer

Next.js / MERN, mobile apps, and API-first microservices

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Data & Knowledge Management

Document ingestion, RAG pipelines, embeddings, knowledge graphs

Security, Privacy & Compliance

Enterprise generative AI must be safe by design. We implement least‑privilege access, encrypted storage, and audit-friendly logs.

For regulated industries, we support GDPR-aligned data handling and privacy-by-design patterns like PII masking, role-based access, and retention policies.

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Least-privilege access

Role-based access controls and encrypted storage

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Audit-friendly logs

Comprehensive tracking for sensitive actions

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GDPR-aligned data handling

Privacy-by-design patterns for regulated industries

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PII masking

Data minimization and retention policies

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Prompt injection defenses

Secure tool execution and content filtering

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Human-in-the-loop review

Where needed for critical decisions

Engagement Models & Timeline

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1–2 weeks

Discovery Sprint

Scope, architecture, data audit, KPI + evaluation plan.

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2–6 weeks

MVP Build

First production-grade RAG/agent prototype with monitoring.

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Ongoing

Scale & Optimize

Improved retrieval, eval automation, cost reduction, and new workflows.

Frequently Asked Questions

Ready to ship a production-grade system—not a demo?

Talk to InnovariaTech about Generative AI Solutions for your product or internal teams. We'll recommend a practical architecture (RAG, agents, or fine-tuning), define success metrics, and map a realistic timeline.

No commitment required • Expert guidance • Free consultation