Proven Impact of3RIVE TECHNOLOGIES

The Challenge

The firm's onboarding process had grown the way every mature firm does: a rule at a time, a system at a time, a jurisdiction at a time. By the time 3Rive walked it with the people who run it, the end-to-end journey from first contact to an open, billable matter comprised more than 200 discrete processes and sub-processes.

Some of those steps are regulatory and non-negotiable. Know-your-client and AML checks under the rules of each jurisdiction. Sanctions and politically-exposed-person screening. Conflict checks against the firm's entire client and matter history. Engagement letters and terms. Source-of-funds enquiries. Others are operational: client and matter setup in the practice management system, intake records, workspace creation in the document management platform, billing configuration, and team assignment.

Each step touched a system. Each system had its own interface, its own login, and its own owner. Between them sat email, spreadsheets and people, carrying the handoffs. Fee-earners logged into systems they had no wish to learn. Risk and compliance re-keyed what new business intake had already captured. Finance waited on both. And because the real path ran through workarounds rather than the version on the intranet, nobody could say with confidence how long onboarding took, where it stalled, or which of the 200 steps were adding control and which were adding only delay.

The firm's leadership wanted onboarding that was faster for fee-earners and clients, demonstrably compliant across every jurisdiction, and visible end to end. The question was whether AI could be put to work on a regulated process without weakening the controls that make it regulated.

The Solution

3Rive's answer is an AI-assisted matter-start flow: a network of specialised agents that together carry a client and matter from first instruction to open and billable, inside the firm's existing systems and under the firm's existing controls.

1. 1

   Discovery First: Map the Real Process

   The engagement began with structured discovery rather than a product demonstration. In a first session with the people who own onboarding day to day, new-business intake, risk and compliance, finance and programme leadership, 3Rive walked the journey as it actually runs, stage by stage, including the manual steps and the workarounds. The output was a validated end-to-end process map of more than 200 processes and sub-processes, a register of every system in the onboarding chain and the data each holds, and a shortlist of the points where a single assisted flow would save the most time.

   A second, technical session went under the systems that the first had pointed to: the practice management, intake, compliance, conflicts, document management and identity platforms. For each, 3Rive established what integration surface existed, the authentication model, the data model, and the information-security and data-residency constraints that apply across the firm's jurisdictions. The output was an integration capability matrix per system, and the constraints that scope the design. A playback session then put the findings, a proposed concept and a recommended first step in front of the firm's leadership.

2. 2

   The Design: A Matter Onboarding Agent Network

   Rather than one monolithic AI, the design is a coordinated network of agents, each responsible for a bounded part of the flow, orchestrated by the firm's own rules.

   The Agent Network

   • Intake agent. Captures the instruction, in plain language or from an inbound email or form, and structures it: who the client is, who the parties are, what the matter is, which jurisdictions it touches, and which of the firm's onboarding paths therefore apply.
   • Client due diligence agent. Gathers and pre-validates KYC and source-of-funds information against the requirements of each relevant jurisdiction, assembles the evidence pack, and flags gaps for the compliance team rather than attempting to make the regulatory judgement itself.
   • Screening agent. Runs sanctions and PEP checks and surfaces results with the reasoning attached.
   • Conflicts agent. Searches the firm's client and matter history across all jurisdictions, proposes a conflicts view with the supporting matches, and routes it to the right partner for clearance.
   • Matter setup agent. Creates the client and matter records in the practice management system, provisions the document management workspace, configures billing, assigns the team and generates engagement terms from the firm's approved templates, once the preceding checks are cleared.
   • Orchestration layer. Sequences the agents according to the firm's rules: what must complete before what, who approves at each gate, what is logged, and what happens when a check fails or stalls.
3. 3

   One Pane for the Fee-Earner

   The principle throughout is that AI does the gathering, assembling, checking and routing, and humans make the decisions that regulation requires humans to make. Every approval that existed in the 200-step process still exists. What disappears is the re-keying, the chasing, the waiting and the logging into six systems to do it.

   The fee-earner sees none of the machinery. They start a matter from inside Microsoft Teams or their normal working environment, in plain language, and the flow comes back to them with progress, questions and decisions as they arise. The request executes as the signed-in user through the firm's identity platform, with no service accounts and no shared credentials, and every action is logged against the person who authorised it. The architecture draws directly on the integrated AI layer 3Rive built and runs for a global top 30 insurance-led firm across its practice, finance and people systems.

4. 4

   Built for Multiple Jurisdictions

   An international firm cannot run onboarding as a single global process. The agent network carries jurisdiction as a first-class attribute: which checks apply, which data can be held where, and which approvers are required are resolved per matter, per jurisdiction, from the firm's own rulebook. Data-residency constraints identified in discovery shape where each agent runs and what it is permitted to move.

The Approach

• Walk the real process, not the documented one. Map every step, system and handoff with the people who run onboarding, before proposing anything.
• Establish what the systems can support. Integration surface, authentication, data model and residency constraints per platform, so the design is grounded in what is possible.
• Decompose into agents, not monolith. Bounded agents for intake, due diligence, screening, conflicts and setup, orchestrated by the firm's rules.
• Keep every human decision that regulation requires. AI gathers, assembles, checks and routes. People approve.
• Put one pane in front of the fee-earner. Plain language in; progress, questions and decisions. No new system to learn.
• Treat jurisdiction as a first-class attribute. Checks, data handling and approvers resolved per matter from the firm's rulebook.
• Start with a tightly scoped slice. Prove the flow on one part of onboarding in production before extending it across the whole.

Systems and Stack

Systems in scope

Credentials

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