Advisors spending Tuesday mornings writing reports that AI should have written overnight. JPMorgan is building six distinct agent programmes simultaneously. Goldman and Citi deployed Devin across 12,000 engineers. The question isn't whether AI works in financial services — it's which builds matter for your firm.
JPMorgan is building six distinct agent engineering functions in parallel. Goldman Sachs and Citi deployed Devin across 12,000 engineers. Per Accenture, 76% of banks plan to grow tech headcount specifically because of agents. Every one of these can be built for your firm.
Performs entity resolution across multiple data sources, runs sanctions screening against OFAC and international watchlists, conducts adverse-media searches, assesses risk scores against your firm's risk appetite, and drafts Suspicious Activity Reports for compliance officer review. Every routine step automated. Compliance team handles the judgment calls.
Summarises client portfolios, pulls relevant market context, drafts the meeting agenda and talking points, writes follow-up notes and action items, and prepares personalised client communications — all before the advisor sits down. The advisor's time goes to the relationship, not the preparation for the relationship.
Collects and validates application documents, verifies income and identity, runs fraud checks, assesses against lending criteria, and routes to the appropriate underwriting path — without a processor manually handling each step. Turnaround times drop from weeks to days. Processor capacity scales without headcount.
Pulls earnings filings, builds financial models, runs valuations, synthesises sector context, and drafts investment committee memos and client-facing research notes. The analyst reviews and adds judgment — they don't build the model from scratch or write the boilerplate sections that consume half their day.
Reviews flagged transactions, builds the case file from linked accounts and transaction history, identifies patterns, cross-references against known fraud typologies, and drafts the disposition report for investigator sign-off. Investigation throughput scales without investigator headcount scaling with it.
Watches model performance metrics and drift indicators in real time, flags breaches against risk appetite thresholds, generates the model risk memo, and escalates to the model risk team with supporting analysis. The team responds to flagged issues rather than monitoring dashboards all day waiting for something to happen.
Structured builds with defined scope, timeline, and starting price. These run alongside agent deployments or ahead of them.
The CRM and client intelligence layer — pipeline, onboarding, review processes, and the meeting prep that currently eats advisor time.
Client relationships spread across individual spreadsheets and email. No firm-wide visibility on AUM, review dates, or relationship health. Pipeline is whoever can remember it.
Full client and pipeline visibility across every advisor. Review dates and AUM tracked centrally. Nothing falls through the gap again.
Annual reviews missed because nobody is tracking which clients are due. Rebalancing opportunities spotted too late or not at all.
Every review date tracked and flagged automatically. Rebalancing triggers fire when portfolios drift outside tolerance. Advisors engage proactively instead of reactively.
Onboarding taking 2–4 weeks of manual document collection and verification. New clients frustrated before the relationship has properly started.
Onboarding time cut to days. Documents collected, verified, and processed without manual chasing. First impression becomes a competitive advantage.
Advisors spending an hour before every client meeting pulling portfolio data, checking notes, and writing talking points that could be generated automatically.
Meeting brief generated automatically — portfolio snapshot, relevant market context, last conversation summary, suggested agenda. Advisor reviews in 5 minutes, not 60.
For growing the book — pipeline automation, referral management, and the client-facing portal that signals a professional-grade operation.
Inbound enquiries treated equally regardless of AUM potential. High-value prospects getting the same response time as low-value ones. Pipeline visibility is a spreadsheet nobody trusts.
Prospects scored and prioritised automatically. High-AUM leads fast-tracked. Pipeline visibility is real data, not best guesses.
Accountants, solicitors, and IFAs referring clients informally. No tracking of which referrers are most valuable. No structured touchpoint system to maintain those relationships.
Every referral source tracked and scored. Touchpoint cadence runs automatically. Best referrers deepened. Cold ones caught before they go quiet.
Clients calling to check balances, request statements, or ask questions that a portal would answer instantly. Every call is advisor time on admin, not advice.
Branded client portal with real-time portfolio visibility, document vault, and automated statement delivery. Inbound admin calls drop significantly. Client satisfaction scores rise.
For managing the documentation, audit trails, and client reporting that regulators require and advisors resent spending time on.
Compliance documentation created manually and inconsistently. Audit trails incomplete. The next regulatory review will find gaps that could have been prevented with proper systems.
Every client interaction logged automatically with appropriate compliance metadata. Audit trail complete and defensible. Regulatory reviews become manageable rather than stressful.
Advisors spending Tuesday mornings writing quarterly reports. Same structure, different numbers, every quarter. Hours of senior time on work that follows a template.
Reports generated automatically — portfolio data, performance commentary, market context, and personalised notes. Advisor reviews and signs off in 10 minutes. That is Tuesday morning back.
For mortgage brokers, insurance brokers, and lending businesses — the application, underwriting, and document chase workflows that define processing capacity.
Brokers manually collecting client data, running quotes across multiple providers, assembling comparison documents. The same process, every client, every time.
Data collected once, quotes run automatically across providers, comparison document assembled and ready. Broker reviews and advises. Time per application cut by 60–70%.
Processors chasing the same missing documents from the same applicants for weeks. Applications stalling not because of credit decisions but because of administrative gaps.
Automated document chase sequence runs without processor involvement. Applications that stall get unstuck automatically. Pipeline velocity increases without adding headcount.
Most firms start with a Starter build, see results in 3–4 weeks, then scope what's next from a position of confidence.
One focused build. Meeting prep automation, lead scoring, or referral tracking — results before you commit to anything bigger.
CRM at the core with connected client management, compliance workflows, and at least one AI agent. The firm starts operating like a significantly larger business.
Custom agents, deep integrations with portfolio management and compliance systems, regulatory reporting automation, and ongoing optimisation.
They understood how our business actually works and built something our team uses every single day.
Financial services implementations involve regulatory obligations, sensitive client data, and compliance requirements that most development teams configure incorrectly. Shivam Kapoor and Sonam Malhotra are active on every project — compliance configuration is built into every build from day one, not retrofitted at the end.
Free audit. We map which agents and implementations fit your specific firm, in what order, and what outcome to expect from each one.
Financial services GCs, compliance counsel, and legal teams handling FCA or SEC matters share almost identical document intelligence and compliance monitoring requirements.
Explore 11 implementations →Fintech companies and financial data platforms — the commercial RevOps and CRM layer is closer to SaaS than to traditional financial services operations.
Explore 11 implementations →Real estate investment firms, mortgage brokers, and property finance businesses share the same CRM architecture and compliance layer as financial services firms.
Explore 11 implementations →· Amroar Technologies · All Industries