From data room to close. One infrastructure.
Find what matters in the target's files during diligence. After close, carve the business cleanly from the same index. Same data layer. Same AI agents. Same audit trail.
The target's data room has thousands of documents. Your model ran on a sample. The contract that breaks the deal is in the files you did not see.
Deal timelines do not allow for manual document review at scale. Traditional diligence teams sample. AI wrappers pre-chunk and hope the right chunks get retrieved. Both approaches miss the outlier. And the outlier is what kills deals or costs hundreds of millions after close.
Carve-outs have the same problem in reverse. Two businesses share a file system. At close, you need to split them cleanly. Mislabeled files end up at the wrong company. Customer lists leak. Contracts orphan. That is a deal-closing problem and a regulatory problem.
Every document. Every page. Ingested the same way.
Octosight ingests the full data room and builds both full-text and semantic indexes. No sampling. No selective review. The pipeline is the same whether the data room has 10,000 documents or 10 million. Extraction, parsing, indexing are deterministic, auditable, and ready for both human reviewers and AI agents.
Ask the questions that break the deal.
Unusual indemnities. Change-of-control clauses. Outlier contracts. Pension exposures. Customer concentration. Octosight surfaces the documents that contain them, with the page and paragraph where each hit lives. Agents query the same index your analysts do. Nothing is retrieved from a summary of a sample.
Carve with precision. Record everything.
At close, classify and route files by business, by customer, by contract scope. Migrate records to the right legal entity with classification and approval recorded. Every action tied back to the finding. The audit trail is the disclosure schedule.
One mislabeled customer list, one orphaned contract, one missed change-of-control clause can cost a deal, or cost the acquirer hundreds of millions after close. The infrastructure that finds it in diligence is the same infrastructure that splits it cleanly at separation.
The same infrastructure runs both sides of the deal.
Find what matters before you sign.
Full-text and semantic search across the data room. Outlier detection across contracts, HR records, customer files. AI agents surface patterns and anomalies. Humans confirm. Every finding is recorded.
Split the business cleanly after you close.
Classify every file by business, entity, or scope. Route records to the right system. Redact or remove what should not transfer. The index from diligence becomes the foundation for separation.
Most platforms handle one phase or the other. Octosight handles both with the same index, the same agents, and the same audit trail. The second phase is already staged by the time the first one ends.
- From sampling to full coverage. "We looked at the important ones" becomes "we looked at all of them." Every document in the data room read by the same infrastructure.
- From manual review to agent-assisted review. Agents surface the patterns. Analysts confirm and decide. The ratio of human hours to documents reviewed flips.
- From two platforms to one. Diligence and separation run on the same index. The work that produced the deal produces the integration plan.
- From report to audit trail. The record of what was found, what was decided, and what was done is the deliverable. It ships with the close.