Welcome to {CK} Web Solutions

We evaluate the latest AI models and run small, low-risk experiments to help you decide whether investing in AI makes sense for your business.

OUR SERVICES EXAMPLE CASE STUDIES

WE OFFER

Practical AI Expertise Beyond Generic Models

AI Model Selection & Feasibility Testing

"Imagine testing whether an AI idea actually works — before committing time, money, or integrating it into your systems."

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Multi-Step AI Systems

"Imagine an AI solution where each task is handled by the model best suited for it — not one model trying to do everything."

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AI Connected to Your Data

"Imagine customers asking intelligent questions about your inventory or operations — without exposing your real-time data publicly."

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Working at the AI Frontier — Beyond Generic Models

"Imagine a problem that was difficult or impossible to solve a few months ago suddenly becoming straightforward."

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AI Performance & Cost Optimization

"Imagine getting accurate answers fast — without paying for more intelligence than the task actually needs."

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Transparent AI Cost Tracking

"Imagine knowing exactly what an AI system will cost — before it's ever used at scale."

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Selected Case Studies

Here are just some of the case studies we conducted to confirm or rule out AI feasibility for real-world business problems.

Employee Navigation Training Using 3D Store Mapping

We conducted a study to explore whether AI-assisted indoor navigation could be used as a training tool for new employees in large retail environments. Click see results below to learn more.

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3D Store Navigation - Employee Training Tool

Customer Demographics from Video Analysis

We conducted a feasibility experiment to explore whether existing store camera footage could support high-level demographic analysis without facial recognition or personal data. Click see results below to learn more.

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Video Analytics - Customer Demographics

AI-Powered Real Estate Photo Enhancement

We explored whether the latest generative image models could automate professional real estate photo retouching, including window exposure correction and interior enhancement.

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Before - Original Photo After - AI Enhanced Before After

Smart Recommendations Powered by Your Database

We built an AI-powered search experience for bookstores that turns a simple ISBN inventory into an intelligent, customer-facing discovery tool. Click see results below to learn more.

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AI Book Recommendations

Local Speech-to-Text for Faster AI Prompting

We built a small internal tool to add fast voice input to AI tools that don't support dictation, saving us hundreds of hours of productivity per year.

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Voice-to-Text Chrome Plugin

Choosing the Right AI Model

We test AI models on real-world tasks to reveal strengths, limits, and the best fit for your use case.

Vision & Image Analysis

Models capable of interpreting images, identifying objects, and extracting visual meaning.

Models we work with:

  • OpenAI — GPT-4o (image understanding & description)
  • OpenAI — GPT Image 1.5 (image generation & editing)
  • Google — Gemini Pro Vision (multimodal reasoning)
  • Meta — SAM 2 (object segmentation & tracking)
  • Ultralytics — YOLO11n (real-time object detection & tracking)
  • OpenCLIP — ViT-B-32 (appearance-based classification)

Audio Analysis & Generation

Models for analyzing, transcribing, separating, and generating audio — from speech recognition to real-time voice conversations.

Models we work with:

  • Meta — SAM Audio (sound segmentation & isolation)
  • OpenAI — Whisper (speech recognition)
  • Nvidia — Parakeet-v2 (fast transcription)
  • Google — Gemini Live API (real-time voice conversations)
  • ElevenLabs — Voice cloning & text-to-speech
  • Resemble AI — Chatterbox (open-source TTS)
  • Meta — Demucs (music source separation)

Semantic Search & Retrieval

Models optimized for semantic embeddings and similarity search across large document collections.

Models we work with:

  • OpenAI — text-embedding-3-large (high-accuracy search)
  • Google — Gecko (fast multilingual embeddings)
  • Cohere — Embed v3 (multilingual retrieval)
  • Voyage AI — voyage-3 (code & technical docs)
  • Hugging Face — BGE-M3 (open-source multilingual)

Text & Language Understanding

Models designed to understand, summarize, classify, and reason over written language.

Models we work with:

  • OpenAI — GPT-4o (complex reasoning & analysis)
  • OpenAI — GPT-4o-mini (fast, cost-effective tasks)
  • Anthropic — Claude 3.5 Sonnet (long documents & coding)
  • Google — Gemini 2.0 Flash (speed & multimodal)
  • Meta — LLaMA 3.3 70B (open-source, self-hosted)

OCR & Document Structure

Systems for extracting text and layout from scanned documents, PDFs, and photos.

Models we work with:

  • Google — Document AI (forms & invoices)
  • Microsoft — Azure Document Intelligence (structured extraction)
  • Amazon — Textract (tables & handwriting)
  • Mathpix — Snip (equations & scientific docs)
  • Tesseract — v5 (open-source OCR)

Classification & Pattern Detection

Models used to tag, route, score, or flag data at scale.

Models we work with:

  • OpenAI — Fine-tuned GPT-4o-mini (custom classifiers)
  • Google — Vertex AI AutoML (no-code training)
  • Hugging Face — SetFit (few-shot classification)
  • XGBoost — Gradient Boosting (tabular data)
  • Scikit-learn — Random Forest (lightweight patterns)

Reasoning & Validation

Models used to verify, filter, and sanity-check outputs from other systems.

Models we work with:

  • OpenAI — o1 (complex multi-step reasoning)
  • OpenAI — o3-mini (fast logical validation)
  • Anthropic — Claude 3.5 Sonnet (fact-checking & analysis)
  • Google — Gemini 2.0 Flash Thinking (chain-of-thought)
  • DeepSeek — R1 (open-source reasoning)

Many real-world problems require combining several of these capabilities into a single workflow. We help you choose the right models for each step — balancing accuracy, speed, and cost — and test whether the approach holds up before it’s ever deployed.

OUR PROCESS

Step 1

Problem Discussion

We start with a short conversation to understand the problem, constraints, and why existing approaches may not be working.

Step 2

Focused AI Experiment

We design and run a small, contained experiment using real data to test feasibility, accuracy, cost, and limitations.

Step 3

Clear Outcome

You receive a clear assessment of what works, what doesn't, and whether the idea is worth pursuing further.