Make the governed path the fastest path.

It depends which step is actually failing. If the bottleneck is producing the contract document — slow, inconsistent, assembled by hand from CRM data — then document generation solves it and CLM is a much larger commitment than you need. If the bottleneck is what happens around the document — clause control, approval queues, negotiation history, renewals nobody sees coming — that is CLM, and document generation alone will not touch it. A useful test: if your legal team can describe the problem without mentioning the document itself, you are looking at CLM.

Conga CLM integrates natively with Salesforce, so agreements relate to the records that generated them — opportunities, accounts and quotes. That connection is what makes the useful reporting possible: contract value against pipeline, renewal exposure by account, cycle time from opportunity stage to execution. Conga also connects to other systems via APIs where the contract estate reaches beyond Salesforce. The design work is deciding which object owns what, because an agreement model that duplicates account data rather than relating to it causes problems for years.

Pre-approved language, organised so it can be found and applied automatically. In practice that means a clause taxonomy, a preferred position for each clause plus the fallback positions legal will accept, and the conditions that decide when each one is included — jurisdiction, contract value, product, entity. Conga CLM can include or exclude clauses automatically based on those conditions, and it tracks clause usage, which is how you eventually learn which terms get negotiated most. The library also needs its own ownership and versioning, or it drifts the same way loose templates do.

Yes, and the sequencing matters more than the volume. Moving files is straightforward; the work is capturing structured metadata — parties, dates, values, renewal terms — so the migrated estate is reportable rather than just stored. We normally prioritise active and high-value agreements first, since those are where renewal and obligation tracking pays back immediately, and handle the long tail afterwards. Where the estate is large enough that manual extraction is impractical, AI extraction is the route: see Conga AI and contract intelligence.

It will if you automate the process you have. Most approval bottlenecks are not a technology problem — they are a matrix that routes everything to everyone regardless of value or risk, with no delegation. Implementing that faithfully just makes the queue electronic. We redesign the routing as part of the work: risk-based bands, approvals triggered by clause deviation rather than by default, parallel routing where sequencing is not required, and delegation so absence does not stall the quarter. The control usually goes up and the cycle time comes down, because fewer things need approving at all.

Yes, and where an organization runs both, designing that handoff is usually the highest-value piece of the whole programme. The accepted quote carries the commercial terms — products, quantities, pricing, duration — and those should populate the agreement rather than being re-keyed into it. Done properly it also closes the loop the other way, so the executed contract is what renewal and billing work from. If you are implementing both, we sequence them so the shared data model is designed once: see Conga CPQ implementation.