When is search or AI core enough to need a specialist CTO?

When the quality of your search, ranking, retrieval, or AI output is something customers feel — and a generalist cannot tell you why it is good or bad. If relevance, recommendations, RAG answers, or model behavior are part of the product experience you are judged on, the architecture decisions underneath them are too consequential to leave to vendor defaults or guesswork. That is the line.

Can you help with RAG, vector search, agentic search, and LLM architecture decisions?

Yes — this is the center of our practice. We work on agentic search, retrieval-augmented generation, vector and hybrid search, relevance tuning, evaluation and gold-standard testing, model and vendor selection, and the build-versus-buy calls at the AI layer. Search and retrieval is a core part of the Develomentor bench — it is where our practitioners have built their careers, not a capability bolted on when AI became fashionable.

Do you build the system, or only advise?

Both, depending on what you need. Some engagements are senior judgment — architecture, evaluation, vendor strategy, hiring — layered on top of your existing team. Others are project-based builds where the Develomentor team delivers the search or AI pipeline end to end. We scope the right shape on the discovery call.

We already have strong engineers — what does a fractional CTO add?

Strong engineers build what they are pointed at. A search and AI specialist at the leadership table makes sure they are pointed at the right architecture: the retrieval design that will scale, the evaluation discipline that tells you whether quality is actually improving, and the model and vendor commitments that will not strand you when the tooling shifts again. It is the difference between shipping AI features and shipping AI that works.

How fast can you start a search or AI engagement?

Most engagements begin within one to three weeks of a discovery call, and fixed-scope reviews — a search architecture review, an AI readiness assessment — often start the same week. We confirm fit and a realistic start date on the first call.

Built for Companies Where Search and AI Are the Product

Practitioner depth in search, AI, NLP, and ML at the leadership table — from a team whose careers were built on it.

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Trusted by Leading Organizations

The Challenge

Most fractional CTOs defer to vendors when the conversation turns to search architecture, NLP pipelines, RAG systems, or ML model integration. The Develomentor team does not — because this is where we have spent our careers.

Led by Grant Ingersoll — co-founder of Apache Mahout, core Apache Lucene & Solr committer, OpenSearch contributor, and author of Taming Text, the best-selling reference on search and NLP for software practitioners — Develomentor brings practitioner depth that most consultancies cannot match. Grant founded Lucidworks and built production search systems used by Fortune 500 brands. Our team has worked on search at places like Apple, Reddit, Morgan Stanley, and Lowe’s Home Improvement — companies where search, ranking, and relevance are core to their product experiences.

01

Your fractional CTO is learning on the job when it comes to AI and search

02

Your Gen AI prototype works in the demo and fails in production

03

Relevance directly impacts your bottom line, and no one understands how to improve it

Where We Engage

Independent Evaluation of Your Search & AI Architecture

We review your architecture, retrieval quality, and model choices and tell you what's working, what's expensive theater, and what needs to change. Led by Grant Ingersoll — Apache Lucene/Solr committer, OpenSearch committer, author of Taming Text. No vendor affiliations.

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Implementation, Not Just Advice

Most advisors recommend a stack and move on. Our team builds it. From search infrastructure and NLP pipelines to RAG integration and model deployment, Develomentor engineers own the architecture and write the code — vendor-neutral, with no one to answer to but you.

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Relevance, Ranking, and Quality You Can Measure

We set up the evaluation framework, the offline metrics, and the online tests so your team stops arguing about relevance and starts improving it systematically.

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A Technical Partner Who Can Lead Your Team

When your search or AI organization needs senior leadership during a critical build, our team steps in as fractional CTO or CPO — strategic direction and accountability, without the full-time cost.

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"I can think of no better person to teach a class on search with machine learning than Grant Ingersoll. Through his open source work on the Apache Solr search engine and as a founder of the Apache Mahout machine learning framework, Grant has done more to teach developers about the technology concepts and applications of ML and search than anyone in the business."

Adam Cheyer — Co-Founder of Siri

"Grant has a unique combination of breadth and depth in the search space, from designing a search solution for performance and stability at scale, while also having deep expertise in the internals of the engine, such as text analysis, relevancy tuning, query optimization, and index design. You won’t find a better teacher to provide a solid foundation in the theory as well as how to apply it when building real world search applications."

Tim Potter — Search Engineer, Apple

"Grant is an established expert in the area of Search, Machine Learning, and AI! He has the mind of a researcher, an educator and has demonstrated the applicability of these deep topic areas into real-world products used by enterprises. What better way to learn than from someone who is a published author, a hands-on practitioner, and an industry expert?"

Sameer Maggon — CEO of SearchStax

"Engaging Develomentor was hugely valuable to our team. Grant Ingersoll’s deep expertise and ability to collaborate with our Product and Engineering teams helped focus our project, identify options, and ultimately define a technical strategy that best aligns with the needs of our business and customers."

Nick Burling — VP of Product Management, Nasuni

Capabilities

Search Architecture & Implementation Review

Relevance Engineering

Agentic Search System Design

Hybrid Search Strategies

Gen AI Doc Processing Design

ML Model Integration

Search & AI Builders — FAQ

Common questions from companies where search, AI, or NLP is core to the product.

When is search or AI core enough to need a specialist CTO? When the quality of your search, ranking, retrieval, or AI output is something customers feel — and a generalist cannot tell you why it is good or bad. If relevance, recommendations, RAG answers, or model behavior are part of the product experience you are judged on, the architecture decisions underneath them are too consequential to leave to vendor defaults or guesswork. That is the line.: When the quality of your search, ranking, retrieval, or AI output is something customers feel — and a generalist cannot tell you why it is good or bad. If relevance, recommendations, RAG answers, or model behavior are part of the product experience you are judged on, the architecture decisions underneath them are too consequential to leave to vendor defaults or guesswork. That is the line.
Can you help with RAG, vector search, agentic search, and LLM architecture decisions? Yes — this is the center of our practice. We work on agentic search, retrieval-augmented generation, vector and hybrid search, relevance tuning, evaluation and gold-standard testing, model and vendor selection, and the build-versus-buy calls at the AI layer. Search and retrieval is a core part of the Develomentor bench — it is where our practitioners have built their careers, not a capability bolted on when AI became fashionable.: Yes — this is the center of our practice. We work on agentic search, retrieval-augmented generation, vector and hybrid search, relevance tuning, evaluation and gold-standard testing, model and vendor selection, and the build-versus-buy calls at the AI layer. Search and retrieval is a core part of the Develomentor bench — it is where our practitioners have built their careers, not a capability bolted on when AI became fashionable.
Do you build the system, or only advise? Both, depending on what you need. Some engagements are senior judgment — architecture, evaluation, vendor strategy, hiring — layered on top of your existing team. Others are project-based builds where the Develomentor team delivers the search or AI pipeline end to end. We scope the right shape on the discovery call.: Both, depending on what you need. Some engagements are senior judgment — architecture, evaluation, vendor strategy, hiring — layered on top of your existing team. Others are project-based builds where the Develomentor team delivers the search or AI pipeline end to end. We scope the right shape on the discovery call.
We already have strong engineers — what does a fractional CTO add? Strong engineers build what they are pointed at. A search and AI specialist at the leadership table makes sure they are pointed at the right architecture: the retrieval design that will scale, the evaluation discipline that tells you whether quality is actually improving, and the model and vendor commitments that will not strand you when the tooling shifts again. It is the difference between shipping AI features and shipping AI that works.: Strong engineers build what they are pointed at. A search and AI specialist at the leadership table makes sure they are pointed at the right architecture: the retrieval design that will scale, the evaluation discipline that tells you whether quality is actually improving, and the model and vendor commitments that will not strand you when the tooling shifts again. It is the difference between shipping AI features and shipping AI that works.
How fast can you start a search or AI engagement? Most engagements begin within one to three weeks of a discovery call, and fixed-scope reviews — a search architecture review, an AI readiness assessment — often start the same week. We confirm fit and a realistic start date on the first call.: Most engagements begin within one to three weeks of a discovery call, and fixed-scope reviews — a search architecture review, an AI readiness assessment — often start the same week. We confirm fit and a realistic start date on the first call.

Ready to talk?

Describe your search or AI challenge and we will get back to you within one business day.