Leverage AI-powered workflows to automate document categorization, extraction, validation and structuring.

Critical data is locked in documents, requiring you to rekey data into other systems and applications. ADI ends this wasteful and error prone work by automating the process end-to-end.
Automate Ingestion
ADI integrates with portals, email, file systems and data lakes in order to automate ingestion.
Any Format
ADI supports any unstructured or semi-structured data source, including email, documents, and logs.
Data Validation
Data quality checks can be configured to your requirements.
Data Movement
Data pipelines automate the processing of extracted data to downstream systems and applications.
Human-In-The-Loop
Workflows can be automated from end-to-end, but human-in-the-loop workflows exist for any exception based processing.
Everything in one place, automatically captured and always searchable.
Automated Aggregation
Automate the collection of all your documents across portals and email boxes.
Document Repo
Centralize your documents in ADI’s document repository, which retains full lineage back to source, and includes search and conversational AI capabilities.
Seamless Integrations
with Key Financial Platforms:





Turn unstructured investment documents into clean, usable data instantly.
Extract Data Automatically
Extract crucial entities, dates, amounts, and other details from unstructured documents.
Drive insights
Summarize investment documents and surface actionable insights across your data estate.
Fast-moving data. Zero-tolerance for errors.
Extract Data Automatically
Extract crucial entities, dates, amounts, and other details from unstructured documents.
Drive insights
Summarize investment documents and surface actionable insights across your data estate.
Deployed an AI-driven platform to categorize, validate and extract critical data from investment documents.

Challenge
The fund administrator struggled with extracting critical data from the multiplicity of documents received from GPs, banks, brokers and other 3rd parties. There was a heavy reliance on operations teams to log into portals, download documents, and manually rekey data.
They also leveraged a third party processor for some of the feeds, but persistent quality gaps required manual checking of data before downstream processing.
Solution
ADI built AI-powered workflows to categorize documents and extract required data elements. Data quality checks were performed at the time of extraction in order to catch errors quickly. And pipelines were built to automate tasks, such as real-time calculations, reporting and feeding the general ledger.
Impact
98%
fewer data quality issues
95%
reduction in manual data preparation time
Immediately
rekeying of data