Product

Solutions

Pricing

Resources

Company

Request a demo

AI & data layer

The infrastructure behind everything Cliff does.

A retrieval and reasoning stack built for the depth and structure of manufacturing knowledge, from dense spec tables to superseded revisions.

Request a demo

Multi-model by design

Domain-tuned retrieval

No training on your data

Cliff · data layer

Ingest

PDFs, CAD, spec tables, bulletins

Index

Vector + structured + lexical

Retrieve

Ranked by meaning, not keyword

Reason

Frontier models, grounded prompts

Cite

Every claim links to its source

The reasoning layer behind product expertise at leading manufacturers

The reasoning layer behind product expertise at leading manufacturers

The before

General-purpose AI wasn't built for your unique workflows.

A general model has no idea how your business works. Cliff is engineered for your products, your knowledge, and the way your teams actually use them.

Off-the-shelf AI

Struggles with tables and drawings.

Half the answer lives in spec sheets and diagrams, which general models read as flat text.

Matches on wording, not meaning.

Finds documents that resemble the question, not the ones that actually answer it.

Answers without sources.

Produces a confident response with no link back to a document. You can't verify it.

One general model for every task.

A model built for broad use, applied to precise engineering content it was never tuned for.

Answer fidelity on technical content: Inconsistent

Cliff's data layer

Multi-modal ingestion.

Tables, diagrams, drawings, captions, and prose. Each parsed for what it is before it's indexed.

Hybrid retrieval & reasoning.

Semantic, structured, and lexical retrieval, reasoned over by frontier models with grounded prompting.

Citations enforced.

Cliff grounds every claim in a retrieved source. No source, no answer.

Always current.

New specs, revisions, and bulletins flow in continuously, so answers reflect the latest, not a stale snapshot.

Answer fidelity on technical content: Production-grade

Inside the stack

Purpose-built. End to end.

Every layer of Cliff is tuned for the content manufacturers actually produce, and the answers their teams need.

Parsing for the messy real world.

PDFs, scans, CAD metadata, spec tables, exploded views. All extracted with structure preserved, not flattened to text.

Indexing that knows what it's reading.

Vector indexes for semantic recall, structured indexes for tables and SKUs, lexical for exact-match part numbers.

Reasoning that shows its work.

Frontier models running grounded prompts with retrieved context, forced to cite the passages they used.

What this enables

The hard questions, answered with confidence.

This is where Cliff earns its place, on the technical, structured, edge-case-heavy content where generic tools quietly fail.

Spec lookup

"Voltage range for the auxiliary heat strip on the 2024 RH-1648."

Pulled from a table in a spec sheet, not a paragraph.

Spec lookup

"Voltage range for the auxiliary heat strip on the 2024 RH-1648."

Pulled from a table in a spec sheet, not a paragraph.

Compatibility

"Which condensers pair with the AH-3000 air handler?"

Reasoned across compatibility and revision notes.

Compatibility

"Which condensers pair with the AH-3000 air handler?"

Reasoned across compatibility and revision notes.

Multi-doc synthesis

"Difference between the 2025 and 2026 install requirements."

Cliff compares both manuals and cites what changed.

Multi-doc synthesis

"Difference between the 2025 and 2026 install requirements."

Cliff compares both manuals and cites what changed.

Built right

An AI layer you can stake your business on.

Accuracy you can verify

Every answer links to the exact source it Your team can trust what they're acting on.

Accuracy you can verify

Every answer links to the exact source it Your team can trust what they're acting on.

No training on your data.

Your documents are used to retrieve and ground Cliff's answers, never to train a shared model. Period.

No training on your data.

Your documents are used to retrieve and ground Cliff's answers, never to train a shared model. Period.

Constantly improving.

Cliff improves continuously. The platform gets sharper over time.

Constantly improving.

Cliff improves continuously. The platform gets sharper over time.

The infrastructure behind expert answers.

Built to be trusted with your business. Let's show you how.

Talk to Sales

The sales and service intelligence platform for manufacturers. Your best engineer, available to every team, 24/7.

Privacy

Terms