AI & Generative AI Consulting Services
Expert AI consulting services from a team that ships production AI systems, not slide decks. BigData Boutique helps engineering and product teams plan, build, and operate AI on their own data, from strategy and use-case discovery to generative AI, agents, RAG, and MLOps.
Our AI Consulting Services
AI initiatives succeed or fail on their data foundations. We came to AI from search and data engineering, and it shows in what we ship: systems grounded in your data, with the retrieval and pipelines engineered to hold up in production.
AI Strategy Consulting
Use-case discovery, feasibility assessment, and a pragmatic AI roadmap covering enterprise AI strategy, governance, and adoption. We identify where AI delivers measurable ROI on your data and where it does not, before you commit budget
Generative AI Consulting
Generative AI consulting services covering model selection, prompt and context engineering, fine-tuning, evaluation, and cost control, on AWS Bedrock, Anthropic Claude, OpenAI, and open-source models
Agentic AI Consulting
Agentic AI consulting for teams planning or already running AI agents: architecture reviews, orchestration and tool-calling design, guardrails, and observability. See our AI agent development practice for the full build offering
RAG & Search
Retrieval-Augmented Generation pipelines, vector and hybrid search, and semantic search built on Elasticsearch, OpenSearch, and vector databases. This is the retrieval quality your AI answers depend on
AI Integration & Implementation
AI integration consulting that connects models to your existing products, data platforms, and workflows, with APIs, streaming pipelines, security, and compliance included
MLOps & Production AI
Deployment, monitoring, evaluation, and lifecycle automation for models and LLM applications. See our dedicated MLOps consulting services
Proven in Production
Max Security: SCOUT AI
We built an AI-powered intelligence agent on OpenSearch, AWS Bedrock, and Anthropic Claude that made proprietary intelligence instantly accessible, cutting analyst briefing time by 79% and saving 7 hours per analyst every week. Read the case study.
ScreenSteps: Hybrid AI Search
We designed a hybrid search framework combining Elastic Cloud, AWS Bedrock, Nova, and Cohere V4 that dramatically improved search precision and reduced failed searches. Read the case study.
AI Implementation Services: From Proof of Concept to Production
Most companies that hire an AI consulting company already have a prototype. What they need is the implementation work that makes it reliable, secure, affordable, and owned by their team. That is where our enterprise AI consulting engagements spend most of their time.
AI proof of concept in two to four weeks
A scoped POC on your data with a defined success metric, so the decision to invest is made on evidence. Our AI readiness assessment tells you which use case to start with.
Hardening for production
Evaluation sets, guardrails, access control, observability, cost controls, and failure handling added to an existing POC. Typically six to twelve weeks to a system users can rely on.
Integration with your systems
Connecting models and agents to your data platforms, search, ticketing, CRM, and internal APIs, with the data pipelines that keep the AI current. See RAG development and AI agent development.
Engineers embedded with your team
When the gap is capacity rather than strategy, a forward deployed AI engineer joins your team for a quarter or more and ships the critical path with you.
Fixed-scope project, hours bank, or embedded engineer: see how our engagement models and pricing work.
Why Choose BigData Boutique for AI Consulting?
Data-First AI
Most AI failures are data failures. Our roots in search, streaming, and analytics mean we fix the retrieval, pipelines, and data quality that determine whether AI actually works.
Production Mindset
We deliver systems with evaluation suites, guardrails, monitoring, and cost controls. That is the difference between a demo and a product your customers rely on.
Vendor-Neutral
We recommend the models, clouds, and tools that fit your requirements and budget, commercial or open source, and never the ones that pay us referral fees.
Speed to Value
Our fast-track engagements take AI workloads from ideation to production in weeks, not quarters. See the GenAI & RAG fast track on AWS.
Frequently Asked Questions
What AI consulting services does BigData Boutique offer?
We offer end-to-end AI consulting services: AI strategy and use-case discovery, generative AI consulting, agentic AI consulting and AI agent development, RAG and semantic search, AI integration with existing systems, AI governance, and MLOps for production AI. Engagements range from short strategy assessments to full build-and-deploy projects.
Which AI platforms and models do you work with?
We work with AWS Bedrock and SageMaker, Anthropic Claude, OpenAI, Google Gemini, and leading open-source models, plus the retrieval stack around them: Elasticsearch, OpenSearch, ClickHouse, and vector databases. We are vendor-neutral and recommend what fits your requirements.
How is BigData Boutique different from a general AI consulting firm?
AI systems are only as good as the data and retrieval behind them. We have 15+ years of hands-on search and data engineering expertise, which is why our AI projects reach production: the data foundations are engineered properly, not bolted on.
Do you help companies that are just starting with AI?
Yes. Our AI strategy consulting engagements start with use-case discovery and feasibility assessment on your actual data. You get a pragmatic roadmap with expected costs and ROI before committing to implementation.
Can you take an existing AI proof-of-concept to production?
This is one of our most common engagements. We harden POCs with evaluation frameworks, guardrails, observability, security controls, and cost optimization, typically reaching production within weeks.
How are AI consulting and implementation services priced?
Readiness assessments, proofs of concept, and defined implementation projects are quoted as fixed-scope work. Ongoing advisory runs on a pre-paid hours bank, and longer builds can use a forward deployed engineer embedded with your team at a monthly rate. We do not publish list prices; you receive a written quote, and meet the engineer leading the work, before anything is billed. See our engagement models page for details.
What does an AI proof of concept cost and how long does it take?
A scoped AI proof of concept on your data typically takes two to four weeks and is quoted as a fixed price after a scoping call. It ends with a working prototype, a measured result against the success metric you agreed on, and a plan and estimate for production.
Do you work with enterprises or only startups?
Both. Our enterprise AI consulting clients include banks, security and intelligence firms, and Fortune 100 technology companies, where data residency, access control, and audit requirements shape the design. Startups usually engage us through the AI Launchpad program for a fixed-path route to production.
Related AI Resources: Generative AI Development Services · AI Agent Development · LLM Development Services · MLOps Consulting · Machine Learning Consulting · GenAI on AWS & Bedrock · What is Agentic AI? · RAG Development Services · Forward Deployed Engineers
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