Trust Operations Vocabulary

Composable

A system assembled from independent building blocks rather than bought as one monolith. Blocks can be added, removed, or rearranged as your firm's needs change — without a forced migration or an all-or-nothing vendor bundle.

Block

The smallest independently useful unit in r.Team. Every block has a clean interface and works without requiring any other block. You can deploy one, prove it out, and compose the rest on your timeline.

Reasoning Engine

Private AI that reasons over your firm's connected trust data to answer questions, apply fiduciary rules, and support decisions — with its work shown for review. In r.Team, the Reasoning Engine combines ontology definitions, knowledge-graph relationships, and Agent Studio actions into governed intelligence for trust operations.

Known in engineering contexts as inference; on this site we name the capability by what operators experience.

Private Reasoning Engine block

A frontier-class AI model running privately for one firm — a deployable Reasoning Engine unit. Prompts and data stay inside your boundary — your information never trains someone else's model. Each block exposes a clean interface so it can be swapped or upgraded without touching anything downstream.

Neurosymbolic AI

An approach to artificial intelligence that combines two capabilities: reading and interpreting language the way a trained professional does, and applying explicit, verifiable rules the way a compliance framework requires. In trust administration, this pairing matters because a trust instrument is both a document to be read and a set of obligations to be enforced. A system built on language understanding alone can misread; a system built on rules alone cannot read at all. Neurosymbolic AI joins the two, which is what makes accurate, auditable intelligent agents possible in fiduciary work.

Related: Reasoning Engine, Interpretation Governance, and ontology.

Ontology

A structured model of the entities in your domain and how they relate — accounts, clients, beneficiaries, fees, holdings, conventions, and the links between them. Your ontology is the map that AI and agents analyze.

For a trust company, an ontology captures fiduciary meaning that platforms usually leave in manuals and tribal knowledge. See Ontology Builder.

Knowledge Graph

A graph of live relationships across trusts, accounts, entities, fees, and beneficiaries — the operational picture relational tables struggle to show. In r.Team, the Knowledge Graph instantiates your ontology against real account data so the Reasoning Engine can answer cross-account questions.

Agent Studio

The product surface for deploying task-focused agents as independent units — research, drafting, reconciliation, monitoring, Reg 9 review, and intelligence pipelines. Each agent does one job well and hands work to the next through defined interfaces. See Agent Studio.

Parallel-Run

A modernization method that runs replacement intelligence alongside the legacy trust accounting platform, reconciles results to zero on a nightly (or agreed) cadence, and keeps cutover reversible until you sign off. The alternative to rip-and-replace. See the Parallel-Run Method.

Trust Operations

The arithmetic and control side of the trust department: reconciliation, fee calculation, exception surveillance, tax-lot tie-outs, custodial interfaces, and the controls that keep statements and books examiner-ready. Distinct from — and complementary to — trust administration's document and judgment work.

Fiduciary Role

A governed responsibility in the trust relationship — trustee, co-trustee, investment manager, custodian, protector, or similar — with authorities, duties, and approval thresholds that operations and AI must respect. Ontology Builder treats fiduciary roles as first-class definitions.

Fee Schedule

The contracted rules for how fiduciary and administrative fees are calculated and applied to an account or relationship — tiers, minimums, waivers, and exceptions. Agent Studio can monitor calculated fees against the governing schedule.

Beneficiary

A person or entity entitled to present or future benefits under a trust or related structure. Current, contingent, and remainder interests often differ — and those distinctions matter for distributions, reporting, and Reasoning Engine answers grounded in the Knowledge Graph.

Custodian

The institution that holds assets and produces position, transaction, and cash files consumed by trust accounting and operations. r.Team blocks integrate with custodian feeds rather than replacing them.

Stackable

Blocks and agents combine vertically into pipelines. The output of one is a valid input to the next, so you can build workflows piece by piece — the same way you assemble a portfolio from individual holdings.

Event-triggerable

Blocks and agents activate on real-world events — a custodian file arrives, a client record changes, a threshold trips — rather than on schedules or manual runs. They run their job and go quiet. No polling, no batch windows, no babysitting.

Interoperable

Connects to the CRM, custodians, and reporting your firm already runs. r.Team fits your existing stack rather than replacing it. Each block talks to the others through clean interfaces, not proprietary lock-in.

Inference

Inference — the engineering term for running a trained model over data to produce a result. On this site we call this capability the Reasoning Engine, because that describes what it does for your operators rather than how it works under the hood.

Frontier intelligence harnessing

Putting the most capable current AI to work inside your own controls, governance, and data boundary. Frontier-class capability — privately, on your terms, one block at a time.

Monolith

The all-or-nothing platform model r.Team is the alternative to: one suite, one migration, one vendor's roadmap. You adopt the whole package — including the parts you do not want — and bend your workflow to fit theirs.