IngestScale converts unstructured documents into production‑grade datasets in days, not months, with private, in‑database document‑AI pipelines that scale linearly across your cores and data centers. Process millions of pages per hour and reduce TCO by up to 80–90% versus per‑page cloud OCR plus manual review. Accuracy you can measure. Privacy you can verify.
Most document AI projects stall on two fronts: the cost curve at scale (cloud per‑page fees that spike with forms/tables/queries) and the throughput curve (API quotas, orchestration, and data movement). IngestScale solves both with compiled pipelines (Go/C/C++), in‑database AI, and private deployments that keep data on your infrastructure. The result: order‑of‑magnitude speedups and material TCO reductions, with observable accuracy and auditable outputs.
Linear scaling across cores and data centers; 1M+ pages/hour in benchmarked runs. See Methods.
On‑prem or VPC; data stays under your control.
Pay per validated result, not per page or per feature. Scale doesn’t change the unit price. See pricing.
Field‑level QA, lineage, and validation harnesses for audit and compliance. See Methods.
Discover how IngestScale's fusion of compiled pipelines, in-database AI, and pragmatic LLM use delivers repeatable speed, cost, and accuracy at enterprise scale.
Built in Go with optimized C/C++ libraries for extreme concurrency. Process millions of pages across multiple data centers with compiled kernels and memory-efficient concurrency. Linear scalability means doubling resources doubles throughput.
Our expert team trains ultra-fast CPU and GPU-tailored models with ultra-fast database interfaces. We leverage the most recent models from leading cloud vendors and AI companies, with proven experience delivering consistent quality with high-throughput batch inference.
Custom C extensions for PostgreSQL embed AI models directly in your database. Vector embeddings and cosine similarity enable real-time semantic matching and cross-referencing without data movement.
Models learn document families without manual templates. Extract entities, relationships, and structured data across diverse layouts with context-aware understanding.
Model pragmatism, infra control, and flexible ops to move from prototype to production reliably.
Designed for regulated environments with private deployment and auditability. Your sensitive data never leaves your trust boundary.
For technical decision-makers who want to understand our architecture. Built on the latest AI research with industrial-grade engineering for unprecedented performance.
Reported values include 95% confidence intervals and dataset sizes; see Methods.
Methods overview:
We don’t lead with résumés. We lead with outcomes. Our team knows the operational limits of the newest large models—token windows, latency trade‑offs, context fragmentation, cache behavior, prompt brittleness, and cost dynamics—and how to make them behave at production scale.
See how IngestScale's cutting-edge AI consulting transforms specific business challenges into competitive advantages across industries.
FDDs are lengthy (hundreds of pages) with 23 mandated items in varying formats. Extracting key data from 100+ FDDs manually takes weeks.
IngestScale ingests batches of FDDs and outputs structured datasets of all disclosure items in minutes. Our AI recognizes Items 1-23 across different formats using context understanding.
What used to take analysts days now takes seconds with greater accuracy. Query across hundreds of FDDs for insights or ensure compliance by catching missing disclosures.
Thousands of contracts, loan documents, or SEC filings need analysis for key fields, dates, parties, and obligations across varied legal language.
Our parallel processing handles hundreds of PDFs simultaneously. AI extracts structured data (dates, parties, amounts) and feeds directly into analytics systems.
Consistent, accurate extraction handles varied legal language. Client confidentiality maintained with on-premises deployment.
Legacy document archives, insurance policies, medical records, or compliance documents need digitization and structured extraction at massive scale.
IngestScale's Go-based architecture processes documents across multiple data centers. Custom AI models adapt to your specific document types and business rules.
Transform document archives into searchable, structured databases. Enable real-time analytics and compliance reporting on previously inaccessible data. Full-text search + structured tables delivered as Delta/Parquet or live PostgreSQL/Snowflake tables.
These are just examples of what's possible. Our AI consulting team works with you to design custom extraction solutions for your specific document types, business rules, and integration requirements.
Methods: sample size, sampling plan, document family, infrastructure shape, and acceptance criteria. See Methods.
Whether you have questions about our technology, want to see a demo, or need to discuss a specific use case, our expert AI consulting team is here to help. Your data challenges are unique – let's solve them together with IngestScale's tailored solutions.
We value your privacy. Any information you share will be used solely to assist you with your inquiry and demonstrate how IngestScale can accelerate your data journey. We bill only for validated results that meet agreed accuracy thresholds.