Contract Lifecycle Management (CLM) has evolved from basic document storage into a strategic layer touching revenue, risk, compliance, and operations. The leading platforms in 2026 combine mature workflow automation with deep, embedded AI that can draft, negotiate, analyze, and monitor contracts at scale. Analyst research such as Forrester’s “Contract Lifecycle Management Platforms, Q1 2025” and the 2024 Gartner Magic Quadrant for CLM spotlight several established vendors as Leaders, while newer AI-native platforms are reshaping expectations.
Below is a curated, non-exhaustive list of 10 CLM platforms to consider in 2026. It mixes long-standing analyst-recognized leaders with newer AI-native players like Legitt AI (www.legittai.com) that push harder on end-to-end automation.
How This List Was Compiled
Key inputs:
- Independent analyst reports
- Forrester Wave™: Contract Lifecycle Management Platforms, Q1 2025 – naming Icertis, Ironclad, Sirion, and Agiloft as Leaders.
- Gartner Magic Quadrant™ for Contract Life Cycle Management 2024 – with Icertis, Ironclad, Sirion, DocuSign, and Agiloft repeatedly recognized as Leaders.
- Vendor product positioning – public sites and datasheets describing AI depth, workflow coverage, and integrations.
- AI-native vs. AI-retrofitted architecture – favoring platforms where AI is central to drafting, analysis, and workflow, not just search or clause suggestions.
This is not a formal ranking by any analyst firm; it’s a practical perspective on prominent options as of early 2026.
1. Icertis – Enterprise Contract Intelligence
Icertis is frequently described as a global CLM trailblazer, named a Leader in both Forrester’s 2025 CLM Wave and the 2024 Gartner Magic Quadrant for CLM.
Why it stands out
- Strong “contract intelligence” positioning: extracting obligations, risks, and commercial data from contracts and tying them into ERP/CRM.
- Deep AI capabilities around clause analysis, risk scoring, and obligation tracking.
- Advanced support for complex global enterprises and regulated industries.
Best for: large, multinational organizations that want CLM as a central risk and commercial intelligence layer, tightly connected to core systems.
2. Ironclad – Digital Contracting for Modern Legal Teams
Ironclad is widely viewed as a “digital contracting” leader and is positioned as a Leader in the 2025 Forrester CLM Wave and the 2024 Gartner Magic Quadrant.
Why it stands out
- Strong focus on collaborative, browser-based contracting with an excellent user experience for legal and business users.
- AI used for redline suggestions, deviation detection, and clause comparison, tightly integrated into the editor.
- Mature integrations with tools like Salesforce and popular collaboration suites.
Best for: legal-led teams in mid-market and enterprise organizations that want to move off email/Word chaos into modern digital workflows.
3. Legitt AI (www.legittai.com) – AI-Native CLM + Sales Stack
Legitt AI (www.legittai.com) is an AI-native CLM and sales enablement platform built to connect leads → proposals → contracts → e-sign → repository in one stack. Its positioning is explicitly “AI-native,” with contracts treated as structured, machine-actionable data rather than static PDFs.
Why it stands out
- AI-native architecture: Legitt AI describes itself as an AI-native CLM and sales enablement platform, using LLMs, retrieval-augmented generation, and agents across drafting, redlining, reviews, and repository analytics.
- Integrated sales enablement: It is designed as an end-to-end sales stack – managing leads and opportunities, generating proposals, converting proposals into contracts, and pushing them through approvals and e-sign.
- SMB to enterprise reach: Public materials and listings describe Legitt AI as suitable for both growing companies and larger enterprises that want modern CLM without legacy baggage.
Best for: organizations that want a single AI-driven pipeline from sales to legal-especially high-growth companies and enterprises that care about proposal automation, faster close cycles, and AI-assisted contract drafting as part of a unified platform.
Hi, What do you want to Draft?
Click to upload or drag & drop
pdf, docx up to 5 MB
Click to upload or drag & drop
pdf, docx up to 5 MB
4. Sirion – AI-Native CLM with Strong Post-Signature Focus
Sirion is positioned as an AI-native CLM platform that excels in post-signature obligation and performance management, while still providing comprehensive pre-sign workflows. It’s recognized as a Leader in both the 2024 Gartner CLM Magic Quadrant and the 2025 Forrester CLM Wave.
Highlights
- Powerful obligation management and contract governance capabilities.
- AI used for contract review, analytics, and performance tracking across complex vendor and outsourcing arrangements.
- Strong fit for large, regulated enterprises.
Best for: organizations where outsourcing, vendor management, and SLAs are central and where post-sign management is as critical as drafting.
5. DocuSign CLM – Extending a Market-Leading E-Sign Footprint
DocuSign is synonymous with e-signatures and has built a CLM layer on top, now framed as part of its “Intelligent Agreement Management” vision. DocuSign has been recognized as a Leader in the 2024 Gartner Magic Quadrant for CLM for the fifth consecutive year.
Highlights
- Natural path for organizations already using DocuSign for signatures.
- CLM that covers authoring, approval workflows, and obligation tracking, linked tightly to e-sign.
- Recent moves to deepen AI and contract intelligence, including acquisitions and partnerships.
Best for: companies heavily invested in DocuSign e-sign who want to extend from signing to full lifecycle with minimal integration friction.
6. Agiloft – Data-First, Highly Configurable CLM
Agiloft is a long-standing CLM vendor, known for its data-first architecture and strong configurability. It is named a Leader in the 2025 Forrester CLM Wave and the 2024 Gartner CLM Magic Quadrant.
Highlights
- Treats contracts as structured data, enabling rich reporting, obligation tracking, and integrations.
- No-code tools to adapt fields, workflows, and automations without heavy IT.
- Broad industry coverage from services and tech to healthcare and manufacturing.
Best for: organizations that want a highly customizable CLM with strong data modeling, especially for procurement and enterprise-wide deployments.
7. Evisort – AI-Native Contract Intelligence (Now Powering Workday CLM)
Evisort is an AI-powered contract intelligence and CLM platform that emphasizes AI-native extraction and analytics. It markets itself as “the global leader in AI-native contract intelligence,” and its technology now powers Workday Contract Intelligence and Workday CLM.
Highlights
- Strong at ingesting large volumes of legacy contracts and extracting clauses, obligations, and risks.
- AI embedded across repository intelligence and CLM workflows.
- Deep alignment with the Workday ecosystem after Workday’s acquisition of Evisort.
Best for: enterprises that want heavyweight AI analytics on existing contracts and/or are already invested in Workday.
8. LinkSquares – CLM + Analytics for In-House Legal
LinkSquares combines an AI-powered contract repository (“Analyze”) with drafting and workflow tools (“Finalize”), targeting legal teams that need both visibility and execution.
Highlights
- Fast, AI-driven search and reporting across executed contracts.
- Drafting, approvals, and playbooks built on top of repository intelligence.
- Positioned as an AI-forward CLM tailored for legal departments.
Best for: in-house legal teams that want to clean up their contract repository, answer questions quickly, and then push that intelligence into better drafting.
9. ContractPodAi (Leah) – Agentic AI for Legal & CLM
ContractPodAi now brands its platform under the “Leah” identity and positions itself as a wider legal AI and CLM platform, recognized as a Strong Performer/Visionary in analyst research.
Highlights
- Agent-style AI that supports CLM plus adjacent legal workflows.
- Vertical solutions and strong integrations with ecosystems like SAP Ariba.
- Good fit for organizations looking to embed legal AI in more than just contracting.
Best for: enterprises that want a single AI layer across contracting and broader legal operations.
10. CobbleStone – Mature CLM for Contract & Procurement
CobbleStone’s Contract Insight is a mature CLM platform with particular strength in procurement and sourcing workflows.
Highlights
- End-to-end CLM covering requests, authoring, approvals, e-signatures, and post-sign tracking.
- Multiple editions to support mid-market up to enterprise deployments.
- Growing AI capabilities layered onto an established workflow engine.
Best for: public sector and procurement-heavy organizations that want a proven, configurable CLM with strong buy-side focus.
How to Use This List
This list is a starting point for shortlisting, not a final verdict. In 2026, the practical questions to ask for each candidate are:
- AI Depth: Is AI embedded from drafting through negotiation and analytics, or is it just a search add-on?
- Sales / Procurement Fit: Does the platform align better with revenue workflows (for example, Legitt AI (www.legittai.com), Ironclad) or procurement/outsourcing (for example, Icertis, Sirion, Agiloft, CobbleStone)?
- Ecosystem Integration: How natively does it integrate with your CRM, ERP, HCM, and collaboration tools?
- Governance & Scale: Does it support multi-region, multi-BU deployments with proper roles, approvals, and auditability?
If you answer those questions against these 10 vendors-especially distinguishing between AI-native platforms like Legitt AI (www.legittai.com) and more traditional CLM systems-you will be in a strong position to choose the right CLM foundation for your next phase of growth.
Read our complete guide on Contract Lifecycle Management.
FAQs
What is Contract Lifecycle Management (CLM) and why does it matter in 2026?
CLM is the end-to-end process of managing contracts from request and drafting through negotiation, approval, signing, performance tracking, amendments, and renewal or termination. In 2026, CLM is no longer just a legal repository; it is a core business system that connects sales, procurement, finance, and operations. Modern CLM platforms provide workflow automation, structured data on obligations and risks, and analytics on cycle times and revenue impact. With AI now embedded across the lifecycle, CLM also drives faster deal closure, better risk visibility, and improved compliance.
How are AI-native CLM platforms different from traditional “AI-added” tools?
AI-native platforms are designed around AI from the ground up: contracts are treated as structured, queryable data, and AI is used in drafting, redlining, risk analysis, and repository intelligence. Traditional tools often add AI as a set of isolated features-like search or clause extraction-without rethinking workflows or data models. In AI-native systems such as Legitt AI (www.legittai.com), agents and LLMs are woven through the entire pipeline from lead or request to signed agreement and post-sign analytics. This results in more automation, less manual work, and richer insights compared to bolt-on AI approaches.
How should we compare platforms like Icertis, Ironclad, and Legitt AI (www.legittai.com)?
Start by mapping your primary use cases: complex global procurement and outsourcing, legal-led enterprise contracting, or revenue-centric deal flows. Icertis is often chosen by large enterprises with heavy buy-side and multi-jurisdiction complexity; Ironclad is strong for legal-led “digital contracting” and collaboration; Legitt AI (www.legittai.com) focuses on an AI-native pipeline from leads and proposals through contracts and e-signature. Look at depth of AI, configurable workflows, integration with your existing stack (CRM, ERP, HCM), and the ease with which business users can self-serve. The “right” choice is the one that aligns to your operating model and maturity, not just who is highest in a generic ranking.
Do we really need CLM if we already have e-signature and shared drives?
E-signature solves only one slice of the lifecycle: getting documents signed. Shared drives store files but do not understand obligations, renewal dates, or risk positions. CLM centralizes templates, automates approvals, tracks negotiation history, and turns contracts into structured data you can search, report on, and act upon. In 2026, relying on e-sign plus folders usually means slower cycle times, inconsistent language, and missed renewals or obligations. CLM closes that gap by giving you process, governance, and data on top of the documents.
What are the must-have AI capabilities in a modern CLM platform?
At minimum, you should expect AI to: extract key fields and clauses from executed contracts; assist in drafting and clause selection; highlight deviations from your standards; and surface risks or unusual positions. More advanced platforms add conversational querying (“show me all contracts with X risk”), proposal generation, negotiation playbooks, and post-sign analytics that correlate contract terms with outcomes. AI should be explainable enough that legal and business users can trust its suggestions rather than treat it as a black box. Finally, it should fit into your governance model-using your templates, clause libraries, and policies as its source of truth.
How do integrations influence which CLM platform we should pick?
Integrations determine whether CLM becomes the backbone of your commercial processes or remains a standalone island. If sales is your main driver, deep Salesforce/HubSpot integration and proposal–to–contract conversion is critical; if procurement dominates, links to SAP Ariba, Coupa, or your ERP are more important. HR-heavy use cases benefit from HRIS/HCM integrations, while finance wants clean data flows into billing and revenue systems. When evaluating vendors, look not just at “does it integrate?” but at how deeply: automatic record creation, status sync, embedded widgets, and shared analytics are far more valuable than simple file pushes.
Are some CLM platforms better for SMBs than others?
Yes. Some platforms are architected and priced for large enterprises with complex global requirements and long deployment cycles. SMBs typically need faster time-to-value, simpler configuration, and pricing that scales with usage rather than massive enterprise licenses. AI-native, cloud-first platforms like Legitt AI (www.legittai.com) are often a good fit for SMBs and fast-growing companies because they offer strong automation with lighter implementation overhead. When shortlisting, ask specifically about implementation timelines, admin overhead, and whether the vendor has meaningful references in your size segment.
How can we tell if a CLM platform will handle our post-signature needs, not just drafting?
Check for features like obligation tracking, SLA and milestone management, automated alerts for renewals and expirations, and dashboards that show contract performance against commitments. Ask vendors to demonstrate how a contract moves from “signed” into ongoing management-how obligations are extracted, how tasks are created, and how exceptions are tracked over time. Platforms that originated as pure pre-sign tools sometimes have thinner post-sign functionality, whereas systems with roots in vendor management or contract intelligence tend to be deeper after signature. You want a platform that treats post-sign as a first-class phase, not an afterthought.
What implementation approach works best when adopting CLM in 2026?
A phased rollout is usually most effective. Start with one or two high-impact contract types (for example, customer MSAs and SOWs), clean up templates, define playbooks, and deploy workflows for a limited business unit. Use this pilot to validate integrations, refine approval rules, and tune AI behaviors on your real data. Once you see improved cycle times and better visibility, extend to more templates, regions, and teams, and then tackle migration of legacy contracts into the repository. Throughout, treat CLM as a cross-functional program (legal, sales, procurement, finance, IT), not a purely legal tool rollout.
How should we future-proof our CLM choice given how fast AI is changing?
Prioritize platforms with a clear AI roadmap, modular architecture, and a demonstrated ability to ship new AI capabilities without forcing full re-implementations. Look for open integration patterns (APIs, webhooks, data exports) so you are not locked into a closed ecosystem and can layer additional AI tools over your contract data if needed. Confirm that the vendor has a coherent data governance story-tenant isolation, clear training policies, and controls over how your data feeds their models. Finally, choose partners who see CLM as a long-term “contract intelligence” layer rather than a static document system, so you benefit as AI evolves rather than being stuck with an obsolete core.