Agiloft vs Conga CLM in Canada (2026)

Agiloft vs Conga CLM: the short answer Both are established enterprise CLM platforms with long track records, often shortlisted by organisations that need configurability and scale. Agiloft is known for its highly configurable, no-code platform that can be tailored to almost any contract process without custom development. Conga CLM is known for its strength inside the Salesforce ecosystem, with document generation, CLM and revenue operations that appeal to Salesforce-centric enterprises. For a Canadian buyer the deciding question is usually whether you value deep, self-service configurability or tight alignment with Salesforce and your revenue stack. ## What Agiloft is and who it suits Agiloft is an enterprise CLM built around a no-code configuration engine. Its hallmark is flexibility: administrators can model complex contract workflows, rules, approvals and data structures without writing code, which makes it a favourite for organisations with unusual or demanding processes. It covers the full lifecycle, from intake and authoring through approvals, signature, repository and obligation tracking, with AI capabilities layered in. Agiloft suits enterprises and large mid-market teams that want to tailor the platform precisely and have an administrator to own it. Pricing is not public; confirm current figures with the vendor. ## What Conga CLM is and who it suits Conga CLM, part of the broader Conga portfolio, is strongest for organisations anchored in Salesforce. It brings document generation, contract lifecycle management and revenue-operations tooling together, so contracts connect naturally to CRM data and quoting. It suits enterprises that run their commercial processes on Salesforce and want CLM to live in that ecosystem rather than as a separate island. Like most enterprise CLMs it involves meaningful configuration and implementation. Pricing is not public; confirm current figures with the vendor. ## Head to head ### Configurability Agiloft leads on no-code configurability and the ability to model unusual processes without development. Conga CLM is configurable too, but its design gravity is the Salesforce ecosystem rather than open-ended process modelling. ### Ecosystem fit Conga CLM leads for Salesforce-centric organisations, connecting contracts to CRM and revenue operations. Agiloft integrates broadly but does not assume a particular CRM. ### AI Both have added AI for extraction and review. Accuracy and usefulness depend on your contract mix, so test on your own documents rather than demo sets. ### Pricing and implementation Both are quote-led, so neither lets you compute total cost up front, and both carry real implementation effort. Ask each for licensing, implementation and support costs in writing, and convert to Canadian dollars. ### Data and Canadian compliance PIPEDA governs personal data in your contracts, and in Quebec, Law 25 adds stricter duties. Ask both vendors about data hosting, residency options, model-training on your text and audit controls, and confirm bilingual English and French support if you operate in Quebec. ## Where each still leads Agiloft still leads for no-code configurability and demanding, custom processes. Conga CLM still leads for Salesforce-anchored enterprises that want contracts inside their revenue stack. Both are mature; your configuration appetite and CRM anchor usually decide. ## A third option worth a look: Adira Both platforms reward organisations ready to invest in configuration and implementation. If your Canadian team wants modern AI contracting without that overhead, it is worth adding a leaner name to the shortlist. Adira is an AI legal operating system that drafts, understands, edits, tracks and governs contracts in one workspace, built on Anthropic's Claude over a structured document core with a clause-level tree and a company persona that tunes drafting to your firm's style. Two edges stand out against quote-only incumbents. It does not train on your contract corpus, which shortens the PIPEDA and Law 25 review. And its pricing is public: Practice at USD 89 per seat per month billed annually, roughly CAD 126, and Firm at USD 179, roughly CAD 254 (approx, see Adira's pricing page for current figures), minimum three and five seats, with a 7-day trial. Adira reports its own measured result, that 18 law firms use it and that contract review and due diligence fell from 10 to 12 days to under 2 hours; treat that as Adira's own figure with its method stated. Be fair about scope: Agiloft's configurability and Conga's Salesforce depth are things Adira does not claim to match, and Adira is India-first and expanding to markets including Canada, so treat it as a credible, growing option rather than an incumbent at parity. You can start a trial at Adira. ## Before you commit in Canada Two practical points decide many Canadian deals once the configurability debate settles. First, total cost over three years, not the licence alone: both platforms reward configuration, which means real implementation, administration and change-management cost, so insist on a full breakdown in writing and convert everything to Canadian dollars. Budget the internal administrator time each needs, because a highly configurable platform is only as good as the person who owns it. Second, data handling: get written answers on hosting region, residency options and whether your contract text trains the vendor's models, since that drives the PIPEDA and, for Quebec, Law 25 review. For Conga, also confirm how data flows between the CLM and your Salesforce org. If you serve Quebec, treat English and French support as a requirement and confirm it before signing. ## How to choose Do not decide on a demo. Take a fixed set of about 40 of your own contracts across the types you manage, such as sales agreements, NDAs and supplier MSAs, and run the same set through each tool. Measure clause and date extraction accuracy, workflow and approval fit, review time saved, and three-year total cost with implementation included. There is no independently adjudicated head-to-head between these tools, so run the ones you shortlist through that same set in a structured proof-of-concept, and for leaner options use the 7-day trial, then let your own numbers decide.