Combine our managed web data pipelines with pre-trained AI models and custom LLM deployments to go from raw web pages to structured insights — without building anything yourself.
Most teams treat web scraping and AI processing as separate problems. We combine them — from crawl to insight in a single managed workflow.
We crawl and extract structured data from any website using our managed scraping infrastructure.
Our AI models enrich that data — sentiment analysis, entity extraction, classification, summarization, or custom inference.
Enriched, insight-ready data delivered to your API, S3, webhook, or database in your preferred format.
Apply any of these models to reviews, news articles, social posts, job listings, or any text or image content we extract.
Predicted sentiment scores (positive, negative, neutral) for any text. Perfect for review monitoring, social listening, and brand health tracking.
Extract names of people, organizations, locations, products, and custom entities. Power your knowledge graphs and entity-based analytics.
Auto-categorize text into 560+ IAB Taxonomy V2 categories or custom taxonomies you define. Great for content routing and analysis.
Surface the most important terms from any text corpus. Great for SEO research, content analysis, and trend detection at scale.
Generate concise summaries using abstractive (paraphrase-based) or extractive (key-sentence) approaches for any length of text.
Identify the language of any text across 97 languages. Essential for routing in multilingual data pipelines and filtering by locale.
Detect objects, scenes, text (OCR), and content classifications from images extracted during web crawls.
For teams that need more than off-the-shelf models, we build and deploy custom AI solutions using foundation models from all major providers.
Starting at $199 for custom model evaluation and deployment.
Book a Consultation →| Factor | Why It Matters |
|---|---|
| Cost per token | Can vary 100× between providers. Wrong choice burns budget fast. |
| Context window | Determines how much data the model can process per request. |
| Fine-tuning support | Not all models support fine-tuning on custom data. |
| Data privacy | Some providers use your data for future training unless you opt out. |
| Self-hosting | Critical for regulated industries (healthcare, finance, legal). |
| Latency | Real-time apps need fast inference; batch jobs can tolerate more. |
Examples of production pipelines we've built for clients.
Yes. Our AI models are available as standalone APIs. You can send your own text or image data for enrichment — you don't need to use our scraping service. That said, the most powerful workflows combine both in a single managed pipeline.
We work with all major providers: OpenAI, Anthropic (Claude), Google (Gemini), Meta (Llama), Mistral, and others. We evaluate models against your specific use case and recommend the best fit based on cost, accuracy, latency, and privacy needs.
Yes. For teams that need full data privacy, we deploy on your own AWS, GCP, or Azure infrastructure — your data never leaves your environment. This is particularly important for regulated industries like healthcare, finance, and legal.
Timeline depends on dataset size and model complexity. A typical fine-tuning project takes 1–3 weeks from data collection through evaluation and deployment. We handle the entire process end-to-end.
Whether you need a simple sentiment layer on top of review data or a full custom LLM deployment, we scope it, build it, and maintain it.
We'll be in touch shortly at info@specrom.com