Reliability via model consensus
CoPallet runs workflows through multiple LLMs (including OpenAI, Gemini, Anthropic) to compare results and assess confidence.
Build your Enterprise Memory Layer
Give AI agents the knowledge to do hypercontextual work.
Real work is messy. Using context is the difference between success and failure.
CoPallet Memory Layer is your enterprise system to store every operating instruction and tribal knowledge. All indexed in a knowledge taxonomy to retrieve the right context at the right time.
We outperform frontier models in head‑to‑head testing
Enterprise Memory Layer organizes context to enable higher accuracy.
Your source of truth for organizational knowledge
The CoPallet Memory Layer is built from your written SOPs, event logs, and history of manual interventions. Memories are automatically indexed and retrieved for relevant tasks.
Composable agent builder
Build your custom AI agent with modular action
and reasoning nodes.
Example use cases
Shipment processing
Order entry
Load building
POD retrieval
Invoice auditing
Customs processing
ASN processing
Contextual accuracy
Connect the dots
Apply thousands of customer-specific rules and tribal knowledge to make inferences. E.g. Procter & Gamble is coded as P&G, consolidate multiple LTL loads for ACME.
Document processing
Handle any document
CoPallet processes document artifacts like different layouts, multipage tables, handwriting, and varying names (e.g. HAWB vs BOL number) with ease.
Integrations, reinvented
Not your average integration
CoPallet uses your TMS/WMS/ERP data to fuzzy-match names, decipher handwriting, and build contextual memories. CoPallet can connect using both API and EDI.
Multi-step planning with Deep Reasoning
For example, perform a credit check, verify insurance, calculate fuel surcharge, and collect facility hours before building a load.
