What we build
A copilot that owns the admin, so the RM owns the relationship.
Each module is a production component — not a proof-of-concept — wired into the RM's existing CRM, portfolio book, and calendar, with guardrails your compliance team can sign off.
Pre-meeting brief generator
Portfolio snapshot, life-event flags, news alerts, and mandate-fit product angles — pulled into a single page the RM reads on the way in, three minutes of prep instead of thirty.
Voice-to-structured meeting notes
On-device transcription scrubs recordings for privacy, then maps speech into the exact fields your CRM expects — objectives, risk tolerance, liquidity, next steps.
Action + opportunity extraction
Commitments, asks, and follow-ups are lifted out as structured action items — owner, due date, and mandate category pre-filled in Salesforce FSC or equivalent.
Follow-ups in the RM voice
Emails and tasks are drafted in the RM's style, in the client's language, and land in the review queue ready to send — a cycle that used to take hours lands in minutes.
Mobile-first for on-road RMs
Works on the phone between meetings — brief generation, voice capture, draft review, and one-tap CRM write-back all from the same app, no laptop needed.
Multi-language · six-language default
EN, BM, ZH (Simplified + Traditional), TH, ID, JA — tone + register matched to household preference. Sensitive drafts escalate to human draft every time.
Where RMs use it
Every RM motion — covered.
Same copilot, tuned per desk. Shared prompt library, per-desk voice fingerprints, and per-household language preferences. Every motion below runs on the same stack; only the guardrails and integrations change.
Private-bank RM desks
Large RM books across HNW and UHNW households — pre-meeting briefs, structured notes, and tone-matched follow-ups across SG, HK, and wider Asia.
EAM + MFO platforms
External asset managers and multi-family offices running on aggregators — copilot plugs into existing custody + portfolio feeds without ripping the stack.
Client-advisor coaching
Structured meeting notes surface coachable moments for team leads — discovery depth, objection handling, and mandate alignment visible across the book.
Next-best-action prompts
Life events, portfolio drift, household milestones, and news alerts generate specific prompts the RM can action — not generic nudges, concrete openings.
Inbound-call triage
Client inbound calls land with a one-screen household context — recent activity, last meeting summary, open actions — the RM picks up already informed.
News-triggered household flags
Market events and household-linked news (family-business IPOs, regulatory changes, obituary + estate) fire proactive RM nudges through the copilot queue.
Model families we deploy
No single model runs the whole copilot. So we compose.
Each family covers a distinct motion — brief generation, transcription, extraction, drafting — composed into a single RM experience with guardrails at every boundary.
Long-context model stitches CRM household data, portfolio positions, news feeds, and prior meeting notes into a structured pre-meeting brief — with guardrails for tone and compliance.
Speech-to-text with speaker diarisation and on-device PII scrubbing, then structured-field extraction tuned to each firm's CRM schema. Whisper / Deepgram options per deployment.
Named-entity recognition combined with intent and commitment detection — lifts asks, promises, and follow-ups as typed action items ready for CRM write-back.
Draft-generation model conditioned on the RM's recent sent mail — cosine similarity scored, tone guardrails enforced, never auto-sends without explicit RM approval.
Data wired into every copilot moment
Every signal the RM already works from — integrated.
Pulled in parallel, normalised into a single household schema, versioned alongside the prompts and guardrails that consume them.
Explainability, not black-box drafts
Every draft has a provenance tag. Every action has an audit trail.
Every email the RM sends, every CRM write the copilot stages, every action extracted from a meeting — all carry the model version, prompt version, voice-fingerprint score, RM review time, and edits applied. Compliance can replay any output, reverse any write.
- RM voice cosine score per outbound draft
- Model + prompt version logged per output
- Customer-language + register auto-verified
- Aligned to MAS Notice 626, HKMA SM-1, local equivalents
Why Axccelerate for RM tooling
Not a prompt wrapper.
A production RM platform.
A generic AI assistant gives you draft emails. Our platform gives you CRM-wired briefs, voice-to-structured notes, action extraction, and voice-matched follow-ups — with provenance on every output.
Pricing
Priced to the desk, not the message count.
Copilot deployments are custom — we scope against your desks, CRM, compliance policy, and languages before quoting.
Glossary
The vocabulary behind every RM motion.
A quick reference for the acronyms that show up in private banking and RM tooling — the terms your desk leads, compliance officer, and platform team will all use.
- RM
- Relationship Manager
The primary client-facing role in private banking and wealth management — owns the household relationship, coordinates product specialists, and carries the book of business.
- Book of business
- RM portfolio of households
The set of household relationships owned by a single RM, typically measured by AUM, revenue, and wallet-share. Book health is the core productivity KPI.
- CRM
- Customer Relationship Management
The system of record for household profiles, interactions, opportunities, and tasks. Every copilot output either reads from or writes back to the CRM.
- Salesforce FSC
- Financial Services Cloud
The wealth-management variant of Salesforce — household data model, mandate workflows, interaction logging, and compliance-aware record-sharing.
- Voice transcription
- Speech-to-text conversion
The process of converting meeting audio into text. Modern systems include speaker diarisation, timestamp alignment, and PII scrubbing before any upload.
- ASR
- Automatic Speech Recognition
The technical term for the transcription model itself — Whisper, Deepgram, Azure Speech, and others. On-device ASR keeps audio local until the RM approves upload.
- Intent extraction
- Classifying what the speaker wants
Detecting whether an utterance is a commitment, a question, an objection, or a request — the signal the copilot uses to lift actions out of free-form speech.
- Entity extraction
- Named-entity recognition (NER)
Identifying named things — products, people, dates, amounts — in transcripts. Underpins how action items get owners, due dates, and mandate tags attached.
- NBA
- Next-Best-Action
The prompt surfaced to the RM: what to do next for a given household based on portfolio drift, life events, mandate fit, and news. Not a generic nudge — a specific opening.
- Pipeline health
- RM book vitality signal
The copilot-derived view of open opportunities, meeting cadence, action-item completion, and wallet penetration across the RM's book — visible to team leads for coaching.
- AUM
- Assets Under Management
The total investable wealth the firm manages on behalf of a household or across an RM's book. The headline metric behind RM compensation and book sizing.
- Wallet share
- Share of household financial footprint
The fraction of a household's total investable wealth the firm actually manages, vs what sits with competitors or self-directed. Growing wallet share is a core RM objective.
- Suitability Review
- Mandate-product fit check
Regulatory-mandated check that each product recommendation fits the household's risk profile, objectives, and mandate. Copilot drafts never bypass suitability workflows.
- Coaching
- RM development review
Team-lead review of RM meeting notes, follow-through, and book health — structured output from the copilot makes coaching sessions evidence-based instead of anecdotal.
Give your RMs back their calendar.
30-minute scoping with a senior engineer and a wealth-platform operator. You'll leave with a desk plan, CRM integration sketch, and realistic timeline — not a sales pitch.