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The Context Layer

Your Manufacturing Operation as Code.

A connected, source-grounded view of the operational information needed for the work: your documents, your system data and the scientific sources your teams rely on, organized by a customer-specific Ontology and a Knowledge Graph that keeps every result linked to its original source, without requiring data migration.

  1. operationSite A · fed-batch culture · product P-14SAP · plant
  2. recipeP-14 master batch record · Rev 3Veeva Vault · controlled document
  3. specificationP-14 · Rev 2Veeva Vault · controlled document
  4. procedurescell culture and harvest SOPs · in forceSharePoint · Document Intelligence
  5. equipmentproduction bioreactor · 2000 L · Site ASAP · equipment master
  6. materialcell-culture feed · lots 2231-A, 2231-B this quarterSAP · material master
  7. certificates2231-A · 0088 · 2231-B · 0091 · on fileOutlook · the supplier's email
  8. compositiondata for lot 2231-B · not in the review setcertificate 0091 · flagged
  9. batchesBR-0410 to BR-0421 · the comparison setbatch records · Document Intelligence
  10. feedsfeed 3 recorded late · BR-0412 · BR-0421batch records · feeding record
  11. deviationsDV-0088 · feed 3 later than planned · openVeeva Vault · deviation record
  12. samplesharvest · lower titer on BR-0412, BR-0421Snowflake · harvest results
  13. literaturefeed timing and harvest titer · 3 studiesPubMed · ScienceDirect
Where the knowledge lives

Knowledge exists across the organization and its partners.

Putting it to use demands work of its own: finding the right information, reconciling what different records say and assembling the evidence needed to begin. Recipes, procedures, batch records and lab reports on paper and in PDFs; materials, suppliers and equipment in SAP; process and sample data in Snowflake; deviations and controlled documents in Veeva Vault; the literature in PubMed. Each names the operation's things its own way, so every question starts by assembling them by hand.

Why was harvest titer lower on BR-0412 and BR-0421?

Documents
  • Batch recordsfeeding records · section 6
  • Master batch recordP-14 · Rev 3 · feeding schedule
  • SOPscell culture and harvest
  • Harvest resultstiter by HPLC · p. 2
  • Certificates of analysis0088 · 0091 · the feed lots
Systems
  • SAPprocess orders · feed lot by batch
  • Snowflakeharvest titer · BR-0410 to BR-0421
  • Veeva VaultDV-0088 · the master batch record
  • SharePointthe P-14 tracker · batches by lot
  • Outlookthe supplier's email · certificates
Scientific sources
  • PubMedfeed timing · harvest titer
  • ScienceDirectcell-culture media variability

Turn time spent finding information into time spent moving forward.

Explore Document Intelligence
The Ontology

A model of how your operation defines and relates its concepts.

Entities, relationships, schemas and vocabulary specific to your operation and the first job, created and tuned by Katalyze around your terminology, processes and use case. Katalyze brings the domain expertise and reusable patterns; the concepts, the names and the relationships are your operation's own.

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P-14

What the operation makes.

Material in SAPProduct on the batch record

P-14 · Rev 3

How a product is meant to be made.

master batch record in Veeva Vaultplanned feed times on the feeding record

P-14 · Rev 2

What a product has to meet to be released.

specification in Veeva Vaultspecification on a certificate of analysis

cell-culture feed

What goes into a product.

material in SAPFeed lot on the feeding record

2231-A · 2231-B

A quantity of a material received at once.

Lot No. on a certificate of analysisbatch in SAP, its word for a lot

BR-0412

One run of a product, through harvest.

Batch No. on the batch recordprocess order in SAP

DV-0088

A departure from the recipe, and what was done.

Deviation in Veeva Vaultsee DV-0088 in a margin note

harvest · BR-0412

What was taken from a batch to test.

Harvest sample on the feeding recordharvest results in Snowflake

3 studies

Published work the operation relies on.

studies in PubMedarticles in ScienceDirect

The Knowledge Graph

A connected map of your operation's entities and their relationships.

Built on the Ontology from the linked data and the source records, with pointers back to the original documents and systems of record. Agents establish ground truth by querying it and validating findings against source evidence; your experts question it in plain language. Katalyze surfaces missing or uncertain information instead of allowing unsupported conclusions to pass silently.

How compliance works

The questionWhy was harvest titer lower on BR-0412 and BR-0421?

made perreleased againstgoverned bymade atmade fromin batchestested byP-14monoclonal antibody · Site ARecipe P-14 Rev 3Specification P-14 Rev 2ProceduresSite AFeed materialLot 2231-ALot 2231-Bthe feed supplierBatches, BR-0410 to BR-0421Deviation DV-0088Harvest samplesLiteraturedocumentssystemsscientific sourcesBatch recordsMaster batch recordSOPsCertificatesSAPSnowflakeVeeva VaultSharePointOutlookPubMedScienceDirect
P-14monoclonal antibody · Site A

Known asMaterial in SAP · P-14 mAb on the batch record · P-14 in the master batch record · P-14 in the tracker

recipemaster batch record · Rev 3Veeva Vault · controlled document
specificationRev 2Veeva Vault · controlled document
batches12 · BR-0410 to BR-0421batch records · Document Intelligence
harvest titerlower on BR-0412 and BR-0421Snowflake · harvest results
deviations1 open · DV-0088Veeva Vault · deviation record
feed lots this quarter2231-A, 2231-BSAP · material master
literature3 studiesPubMed · ScienceDirect
How it is built

Connects without data migration.

Document Intelligence extracts and contextualizes information from operational documents, while Connectors bring in relevant system data, scientific datasets, research publications and other academic sources. Together, these inputs feed the Context Layer. Customer systems remain the source of truth.

Explore Connectors
Knowledge GraphOntologyDocuments · Systems · Scientific sourcesmade perin batchesraisedtested byinformsSAPConnectorProductP-14productMaster batch recordDocument IntelligenceRecipeRev 3recipeVeeva VaultConnectorDeviationDV-0088deviationBatch recordsDocument IntelligenceBatchBR-0412batchSnowflakeConnectorSample12 samplesharvestPubMedConnectorLiterature3 studiesliterature
What runs on it

Each new solution builds on the same platform and Context Layer.

Agents establish ground truth by querying the Context Layer and validating findings against source evidence, then investigate and execute governed work. App Studio lets teams build dashboards and applications from reusable components backed by the same connected information, and search and question it in plain language. Start with one job, Document Intelligence or an Agentic Solution; the context it builds gives the next a head start.

All Agentic Solutions
Context Layer
  • Ontology
  • Knowledge Graph
  • lineage to every source
Agents act on it
  • 01

    Deviation Investigation

    Assemble and validate relevant evidence to investigate possible causes.

    Draws onBatches · Deviations · Recipe · Feeding records

    Explore
  • 02

    Yield Optimization

    Connect recipes, process records, material data and system data to investigate yield performance.

    Draws onRecipe · Feeding records · Materials and lots · Harvest results

    Explore
  • 03

    Raw Material Characterization

    Connect material, supplier and scientific information to investigate variability.

    Draws onMaterials · Suppliers · Certificates · Samples · Literature

    Explore
  • 04

    Tech Transfer

    Assemble process knowledge and supporting evidence to prepare transfer documentation and action plans.

    Draws onRecipe · Procedures · Specification · Sites and equipment

    Explore
Experts ask questions of it
  • 05

    App Studio

    Dashboards and applications from reusable components backed by the Context Layer.

    Draws onEvery entity · Every source

    Explore
  • 06

    Katalyze, the agent

    Search and question connected operational knowledge in plain language; the answer keeps its sources.

    Draws onEvery entity · Every source

    Explore
Results

Put more of your expertise into progress.

What teams put the connected context toward: faster batch release, shorter deviation investigations and more of their experts' time on the science.

See customer results
The ontology layer was already in place. Data ingestion into the intelligence layer was solved.
Sabya DGlobal Head (VP) R&D Data Platforms & Products
Live on your existing stack, not months
2 weeks
Of the pharma top 20 run Katalyze
5
Doses delivered with Katalyze
10M
FAQ

Questions about the Context Layer.

What it connects, how it is built around your operation, and what it changes for the next question. The full set of answers is in the FAQ.

All questions and answers
Book a demo

Give the next question a head start.

Bring the job you want to move forward and the records you'd like connected. Thirty minutes on how Katalyze would do the work, and where your experts come in.

Or, just a quick chat to run through the product, your call.