Relait — AI & automation in investor relations

Quarterly and annual reports are cornerstone communications, but they traditionally take 3–4 weeks of intensive work. Data extraction, table building, narrative drafting, and formatting all happen in sequence, by hand, and each step invites delays and version conflicts. Reviews across finance, legal, and communications stretch the timeline further.

• Data integration — API connectors ingest transactional and financial data straight from source systems, removing manual exports.
• AI-driven drafting — A natural language generation engine, trained on historical reports and the company’s tone guidelines, drafts disclosures automatically.
• Human-in-the-loop validation — Analysts review the AI drafts, focusing on strategic insight and accuracy rather than formatting.
• Automated publishing — Once approved, the system packages reports into PDF and web-ready HTML and distributes them across investor portals and regulatory channels.

Timely announcements are critical, but legal and compliance review cycles hold them back. Drafting a disclosure can take hours of back-and-forth, and social and email updates often trail the official exchange filing, leaving communication gaps.

• Generative AI drafting — Domain-specific language models draft compliant disclosures aligned with ASX and NYSE frameworks in minutes.
• Pre-submission validation — AI modules cross-check each disclosure against exchange rules and flag compliance issues before submission.
• Multi-channel automation — Once approved, announcements publish simultaneously to exchange platforms, investor portals, email lists, and social channels.

Traditional IR relies on mass emails with generic messaging and little feedback on engagement. Social updates are reactive, often posted late, and miss the window on investor sentiment.

• Segmented AI personalisation — AI analyses investor profiles and segments audiences to tailor subject lines, executive summaries, and key insights.
• Real-time engagement analytics — Dashboards show live open rates, click-throughs, and sentiment, so communication can be adjusted on the fly.
• Automated social snippets — Social posts are generated from announcements and published instantly to keep market presence current.

Compliance checks and audit trails are usually manual, line-by-line, with approvals tracked across emails and spreadsheets. That raises risk and makes audits painful.

• AI compliance validation — Automated checks against regulatory requirements flag issues before submission.
• Role-based approval workflows — Digital workflows enforce approvals by role, preventing unauthorised submissions.
• Immutable audit logs — Every draft, edit, and approval is recorded in tamper-proof logs, giving a complete audit trail.

As shareholder numbers grow, inquiries and communications grow with them. Scaling the old way means hiring proportionally more people, driving up cost and complexity.

• Predictive analytics — Machine learning analyses trading patterns and sentiment to flag potential sell-offs or reputational risks early.
• Automated mass distribution — Email and social updates reach thousands of investors at once, with no manual effort.
• AI-powered investor chatbots — Context-aware chatbots answer common questions, drawing on filings and historical Q&A.

Investor communications involve sensitive financial disclosures that demand strict security, precise version control, and controlled access. Manual handling across scattered storage raises the risk of leaks, version drift, and compliance lapses.

• Encrypted cloud repositories — Secure cloud storage with end-to-end encryption protects data at rest and in transit.
• Data masking and tokenisation — Sensitive fields such as shareholder identifiers, holdings, and personal details are masked or tokenised, so they’re never exposed in logs, non-production environments, or to users without explicit clearance. The real values stay encrypted; everyone else sees only what their role permits.
• Role-based access control — Access to disclosures and reports is controlled by role (investors, analysts, legal), so people see only what they’re authorised to.
• Automated versioning — Every document version is saved and tracked, giving an immutable history for audits.
• Investor portals — Secure, easy-to-use portals let investors access current disclosures on demand, reducing ad hoc inquiries.

IR is increasingly expected to be an ongoing dialogue, not a periodic broadcast. The traditional approach has no mechanism for real-time feedback or sentiment analysis, so investor concerns go unaddressed and messaging can’t adapt.

• Interactive investor portals — Two-way portals let investors submit questions, browse FAQs, and get real-time updates beyond static reports.
• AI-powered feedback analysis — NLP aggregates and analyses investor queries, sentiment, and engagement to surface emerging concerns.
• Proactive alerts and dashboards — Real-time dashboards and alerts turn investor sentiment into actionable insight for timely responses.