Institutions running on Karmaflow operate servicing, KYC/AML triage, fraud-alert resolution, and advisory follow-ups as one continuous system. Agents that reason across core, CRM, case history, and the household graph — turning every interaction into context the next one inherits, with a signed audit trail at every step.
Built for regulated teams. Tested in production. Governed end-to-end.
Servicing cases, application replies, secure messages, and maturity nudges accumulate continuously across every region you serve. By Monday morning your queue is hundreds deep — including the fraud escalations and hardship cases that needed an answer by Friday. The cost is not just operational. It is the customer who closed the account, the application that went stale, the household who tried once and gave up.
Institutions running on Karmaflow hold every channel continuously. Servicing questions resolved at the moment they're asked. Application replies triaged in real time. Escalations routed to the right human with full context — not at 9 a.m. Monday, but the moment they arrive. Every action, audit-trail signed.
“We've added a dozen servicing reps in eighteen months. First-call resolution is still 62%. Something in the operating model is broken.”
Your institution's policies, disclosures, and runbooks live across SharePoint, Confluence, the policy admin system, training PDFs, compliance emails, and the heads of three senior reps who've been there since the last core conversion. New hires take ninety days to ramp. Servicing escalates because they can't find the right disclosure fast enough.
The agent answers in seconds, with citations to the actual policy, the actual disclosure, the actual past case where someone resolved this before. It works for customers asking servicing questions. It works for your servicing team. It works for advisors preparing a household review or a fraud analyst working an account-takeover alert.
Reg E provisional credit disclosure script:
1. Provisional credit issued within 10 business days of dispute receipt
2. Investigation up to 45 days (90 for POS / foreign / new account)
3. Required customer language: cite §1005.11 in disclosure
4. If investigation finds no error: written notice + reversal in 5 business days
5. Required artifact: signed acknowledgement stored in case ledger
Your CRM tracks relationship stages. Your core tracks balances. Your servicing system tracks cases. Your online channel tracks logins. None of them talk to each other in a way that says this household is about to walk — here's why, here's what to do, here's the disclosure.
Karmaflow does. The platform reasons across all of those systems at once. It surfaces the patterns that no single tool was ever asked to find — and it does so before the relationship review, not after.
Your CRM tells you what stage a relationship is in. We tell you what's actually moving it — and what isn't.
A relationship agent reasons across origination pipeline, core balances, servicing cases, and customer conversation in one pass. The signals that no single tool was asked to find — surfaced before the relationship review, not after.
Marketing automation is excellent at pushing messages. Engagement tools are excellent at tracking opens and clicks. Neither of them is built to have a regulated conversation.
Karmaflow holds the conversation that follows. A stalled loan application gets a thoughtful reply — and the agent answers the document question, books the walk-through, or escalates to a human only when judgement is required. A CD-maturity nudge gets a question back about options — and the agent qualifies with full context from the household graph, with disclosures attached.
Reads from and writes to Salesforce FSC, nCino, Glia, Five9, Pega, ServiceNow, and the long tail via .
Every agent runs its own workflow on the same shared model. The Application Triage agent knows what the Relationship Co-Pilot saw last week. The Maturity & Cross-Sell agent inherits every signal the Servicing Resolver surfaced over the past six months — and every disclosure served along the way.
A 14-year customer opens secure message at 11:47 p.m. on a Thursday: “I've been with you 14 years. I'm seriously thinking of moving my accounts.”
What happens next is not a script.
A weekly portfolio briefing arrives in a senior banker's inbox on Monday morning. It is not a dashboard. It is a synthesis.
No single conversation revealed it. The graph did. This is what compounding intelligence looks like in practice.
While your team sleeps, the platform works. Not by sending more emails — by thinking.
Not a dashboard. A briefing. With the gaps already flagged, the actions already proposed, and the workday already in motion before anyone arrives.
The same platform serves the advisor preparing for a household review, the servicing rep looking up a disclosure, the fraud analyst synthesising merchant patterns, the banker walking into a quarterly relationship review, the risk leader asking which accounts she should personally call this week.
Five roles. Five different needs. One operating layer that knows the institution well enough to serve all of them — and one audit ledger that records every action.
Every conversation, every case, every maturity, every transaction signal feeds into a single living layer — a graph of households, accounts, advisors, products, behaviours, and outcomes that grows richer with every interaction.
But the graph is not the product. The reasoning is. Agents synthesise across the graph the way your best banker would — reading the tone of a closed dispute, recognising the silence after a rate question, connecting a public life-event signal to a private servicing conversation. They produce briefings, recommendations, and proactive actions that no single tool in your stack could have surfaced — every one with a citation chain and an audit-ledger entry.
A new agent launched on day one starts with the full institutional memory of every agent that came before it. There is no cold start. There is no re-training.
Marcus Reed — primary holder at Household 4471 ($1.2M AUM, 14-year relationship) — is in active institution evaluation. Your retention score is green. Your banker is unaware. Annual review is 22 days overdue.
Marcus opened dispute #4821 twenty-one days ago over a card-not-present charge. Servicing closed it with “provisional credit pending.” Marcus's tone shifted between his first and second secure message — from cooperative to clipped. He used the phrase “this has been going on for months.” The closure was procedural; the frustration was unresolved.
Four weeks ago, Marcus asked your banker about preferential rates after consolidating. The banker replied with the standard rate sheet. Marcus did not reply. The same question pattern preceded cross-sell at three other households. The same post-rate-sheet silence preceded attrition at two recent ones.
Marcus posted a job change to LinkedIn last week — new role, different state. Life events drive 38% of household reallocation decisions. The research agent surfaced this from a scheduled scan of consented public sources tied to your relationship list.
In the secure-message channel six days ago, Marcus asked: “If I were to move funds to a trust at another institution, what's the process?” The data was accessed through the governed integration with full permission scoping, field-level access scope, and audit trail.
Frustration that your servicing team marked resolved. A rate inquiry that went without meaningful follow-up. A public life-event signal. A secure-message question about moving funds. Each signal alone is ambiguous. Together they form a coherent institution-evaluation pattern — one your existing stack was not built to detect.
The graph is the substrate. The reasoning is the workforce. The compounding is yours.
The same Living Intelligence Layer extends beyond servicing and lending into risk, complaint handling, and channel operations — reinforcing that this is a workforce for the whole institution, not a point tool.
Agents read incoming disputes and complaints, dedupe against open cases, draft reproduction with merchant + amount + channel, attach Reg E/Z disclosure framing, and route to the right team — before a human triages a single case.
Pattern detection across servicing cases, fraud alerts, advisor call notes, and complaint logs. Surfaces second-line-ready summaries that no individual signal could have produced — under a reviewable reasoning trace.
The same Servicing Resolver pattern, applied internally. SSO resets, teller workstation access, policy admin questions — answered with the same governance, identity-lock, and citation discipline.
Independent brokers, agents, and producers get self-serve underwriting Q&A, application status, and disclosure support — without consuming your channel team's time on the same questions every week.
Encryption in transit and at rest. Tenant isolation. Field-level access scopes for PII, PCI, and non-public personal information. Redaction by policy. Data residency options for EU, UK, US, and Canadian deployments. GLBA-aligned data handling.
Every action an agent takes is bound to a scoped, identity-locked permission. Tier 1 actions auto-execute under guardrails. Tier 2 actions soft-approve. Tier 3 actions — fund movement, account changes, disclosures with regulatory force — require hard human approval with verified identity and quorum.
Every read, every write, every action, every escalation is logged in the Unified Action Ledger — reconstructible, exportable, and review-ready for regulators, internal audit, second-line, and customer audit requests.
Compliance is not a feature. It is the operating temperature of the platform.
Salesforce FSC, nCino, Glia, Five9, and Pega automate financial workflows. Karmaflow runs autonomous reasoning across them. The two layers are designed to coexist — your existing stack stays, the reasoning layer sits above it with a regulator-grade audit trail.
| Capability | Karmaflow | Salesforce FSC | nCino | Glia | Five9 | Pega |
|---|---|---|---|---|---|---|
| Reasoning across core, CRM, case history, and household graphA single agent reasons over account context, transaction history, and policy before acting. | Native capability | Partial or workflow-style coverage | Partial or workflow-style coverage | Partial or workflow-style coverage | Partial or workflow-style coverage | Partial or workflow-style coverage |
| Cross-encounter memory across households and quartersPattern recognition that compounds across every servicing or advisory contact, not per-session. | Native capability | Not a marketed capability | Not a marketed capability | Not a marketed capability | Not a marketed capability | Partial or workflow-style coverage |
| Voice, chat, secure message, email as one identitySame agent, same memory, same audit trail across every channel — with required-disclosure adherence. | Native capability | Partial or workflow-style coverage | Not a marketed capability | Native capability | Partial or workflow-style coverage | Partial or workflow-style coverage |
| Autonomous action with risk-tier guardrailsLow-risk auto-execute, medium-risk soft-approve, high-risk hard-stop until human confirms identity. | Native capability | Partial or workflow-style coverage | Partial or workflow-style coverage | Partial or workflow-style coverage | Not a marketed capability | Native capability |
| Operates legacy core, LOS, and policy admin without good APIsHuman Interface lets agents drive UI like a human team would — for the long tail of internal systems. | Native capability | Not a marketed capability | Not a marketed capability | Not a marketed capability | Not a marketed capability | Partial or workflow-style coverage |
| Identity-locked sensitive actions with step-up verificationAccount changes, fund movements, and disclosures gated behind verified customer identity and quorum approval. | Native capability | Partial or workflow-style coverage | Partial or workflow-style coverage | Partial or workflow-style coverage | Partial or workflow-style coverage | Partial or workflow-style coverage |
| Unified Action Ledger — regulator-grade audit trail per decisionOne reviewable record per action — what, why, what data, what permission, what disclosure, what outcome. | Native capability | Partial or workflow-style coverage | Partial or workflow-style coverage | Partial or workflow-style coverage | Partial or workflow-style coverage | Partial or workflow-style coverage |
| Stack-neutral — reads from and writes to your existing systemsCore banking, FSC, nCino, Glia, Five9, Pega, Salesforce, ServiceNow — partner, not replacement. | Native capability | Not a marketed capability | Not a marketed capability | Not a marketed capability | Not a marketed capability | Not a marketed capability |
Comparison reflects publicly available product documentation and marketed capabilities as of 2026. The five vendor platforms remain valuable workflow tools — Karmaflow operates above them, reading from and writing to the systems your institution already uses.
Karmaflow is an autonomous AI workforce that operates account servicing, KYC/AML triage, fraud-alert resolution, loan and policy servicing, and advisory follow-ups as one continuous system. Institutions use the platform to deploy agents that reason across core, CRM, case history, and the household graph — turning every interaction into compounding intelligence with a regulator-grade audit trail.
The platform handles the high-volume reasoning-based work; humans focus where their judgement compounds most — exception cases, relationship advisory, and second-line review.
Those tools automate workflows. Karmaflow runs autonomous reasoning across them. A Glia bot answers from a knowledge base; a Karmaflow agent reasons across the household graph, the case history, the transaction signal, and the policy disclosures to decide what to actually do — and then does it, with identity-locked guardrails for sensitive actions.
Your existing stack is a partner, not a competitor. The platform reads from and writes to it through APIs, MCPs, and — for legacy core, LOS, and policy admin systems without good APIs — through , which operates software the way a human team would.
Phase one — first agents live, handling real channels — typically under a week.
Phase two — deeper agents with cross-system integrations and account-graph awareness — typically 2 to 4 weeks.
Selective phase three deployments — managed integrations into custom or legacy systems — run 4 to 12 weeks. We commit to honest ranges, not breathless claims.
Two starting agents: a customer-facing teammate (Servicing Resolver or Fraud-Alert Triage, depending on where the operational pain is loudest) and a staff-facing knowledge teammate that grounds answers in policy, disclosures, and runbooks.
This pair generates immediate operational lift while the household graph begins to populate. Subsequent agents inherit that context and the same audit discipline.
Enterprise security controls with tenant isolation, field-level access scopes for PII, PCI, and non-public personal information, and redaction in transit and at rest. GLBA-aligned, GDPR and CCPA-compliant data handling. Configurable data residency for EU, UK, US, and Canadian deployments.
Every action is logged in the Unified Action Ledger and reviewable by regulators, internal audit, and second-line on demand. Identity-locked sensitive actions: low-risk auto-execute under guardrails, medium-risk soft-approve, high-risk hard-stop until a verified human confirms.
Yes — Salesforce Financial Services Cloud, nCino, Encompass, Calabrio, Glia, Five9, NICE, Verint, Genesys, Zendesk, ServiceNow, Pega, Microsoft Teams, Google Workspace, and dozens more via direct API and MCP integrations.
For legacy core banking, LOS, policy admin, and one-off systems without good APIs, lets agents operate them exactly the way your team does — clicking, typing, navigating menus. No integration build required for the long tail.
Every action is bound to a scoped permission with risk-tier guardrails. Low-risk actions auto-execute. Medium-risk actions soft-approve. High-risk actions hard-stop until a human confirms.
Every action is logged and reversible where reversal is technically possible. Mistakes are corrected, the correction feeds back into the platform's learning signal, and the same mistake doesn't repeat.
Pilots run with clear, customer-defined success criteria over 2 to 4 week evaluation periods. Pricing is usage-based — conversation minutes, model tokens, executed actions — with platform fees that scale with deployment size.
We don't share generic pricing decks because every institution's deployment is shaped by core, channels, lines of business, and regulatory posture. Talk to us and we'll scope a pilot that proves the case before any commitment.
Proprietary concepts you’ll encounter across the Karmaflow platform — defined plainly, so risk, compliance, servicing, and second-line teams reason from the same definitions.
Servicing, lending, fraud — same standard, smaller team.
Member-first servicing with regulator-grade audit on every action.
Advisory follow-ups, suitability, and household reasoning.
Claims FNOL, policy servicing, agent enablement.
Application triage, payoff quotes, dispute resolution.
Fraud-alert resolution, chargeback intake, dispute handling.
Institutions running on Karmaflow operate servicing, risk, and advisory as one continuous system. The work that runs on judgement and reasoning, scaled. The work that requires human wisdom, elevated. Every action, audit-trail-signed.
PHASE ONE LIVE IN UNDER A WEEK · DEEPER AGENTS IN 2–4 WEEKS
REGULATOR-GRADE AUDIT TRAIL · GLBA-ALIGNED · GDPR · CCPA
