Support agents that can actually close the ticket.

• 01

  Transaction dispute intake

  The agent pulls the transaction, the merchant descriptor and the card network's dispute window, drafts the case in your dispute system, and hands a human the decision with the evidence already attached.

• 02

  KYC re-verification chase

  Detects which document failed and why, explains the specific fix to the customer in their language, accepts the re-upload, and re-runs the check — instead of a generic 'documents rejected' email.

• 03

  Collections and payment-plan triage

  Qualifies hardship cases against your policy matrix, proposes an in-policy plan, and books the exception to a human reviewer with the affordability data already summarised.

• 01

  Every answer needs a receipt

  We ground responses in your own documents and return the citation with the answer. If the retrieval finds nothing, the system says so instead of improvising — that refusal path is tested like any other feature.

• 02

  Models never move money

  The LLM classifies, drafts and retrieves. Balance changes, limit increases and refunds run through your existing deterministic services behind an approval step, with the full prompt and decision written to an audit log.

• 03

  Data residency is a build constraint, not a setting

  For RBI, PCI-DSS and SOC 2 scopes we deploy inside your VPC or account with zero data egress, and pick models — including open-weights — that can legally sit where your data sits.

1. 1

   Use-case scoping

   Pick the workflow with the strongest ROI. Define success metrics, guardrails, and integration points.

2. 2

   Tools & memory

   Connect the agent to your real systems — CRM, helpdesk, data warehouse, internal APIs — with auth and audit trails.

3. 3

   Eval suite

   Build a versioned eval set from real conversations so we can prove the agent improves before each release.

4. 4

   Pilot with humans

   Shadow mode → suggested replies → autonomous on low-risk tasks. Humans stay in the loop where it matters.

5. 5

   Production scale

   Monitoring, fallbacks, cost guards, and observability. Weekly improvement cycles based on production data.

• Stripe
• Razorpay
• Plaid
• Salesforce Financial Services Cloud
• Zendesk & Intercom
• Snowflake / BigQuery
• Postgres with row-level security
• Twilio
• Internal core-banking APIs

FAQ

AI agents for fintech: your questions.

• Will the agent ever issue a refund on its own?

  Only if you decide it should, only under a value ceiling you set, and only for reasons on an explicit allow-list. Default configuration is that the agent prepares the refund and a human presses the button. Every path is logged either way.

• How long until it's live on real customers?

  Shadow mode inside a 30-day sprint is realistic — the agent runs against live traffic and drafts answers nobody sends, so you can score it against what your team actually did. Autonomous handling of low-risk intents typically follows 4-6 weeks later, once the eval scores hold.

• How is this different from a chatbot?

  Chatbots reply. Agents act. Our agents call APIs, update records, send emails, schedule meetings — with audit logs and rollback. They take actions in your systems, not just respond in a chat window.

• Which LLMs do you use?

  We pick the right model for the task — Claude Sonnet/Opus for reasoning, GPT-4o for tool use, Llama / open-weights when data residency demands it. We're not locked into any vendor and we'll tell you what's cheapest at your volume.

• RAG for banking and financial servicesRetrieval over circulars, product terms and internal procedure — returning the clause, the revision date, and a link to the page it came from.Read
• AI governance for financial servicesModel inventories, risk classification, evaluation policy and human-oversight design — written to survive an internal audit rather than a conference talk.Read
• Fintech prototype to productionWe take a working fintech prototype and add the things that were never in scope: real auth, migrations, secrets handling, audit logging, and a test suite that survives the next regeneration.Read

• AI agents for healthcare operationsAgents that handle scheduling, reminders, insurance verification and document chase across voice and messaging — escalating anything clinical to a person immediately.Read
• AI customer service agents for e-commerceSupport agents connected to orders, carriers and your returns rules — resolving tracking, exchanges and address changes end to end on Gorgias, Zendesk or Intercom.Read
• In-product AI agents for SaaSAgents that execute inside your product — configuring, importing, drafting and fixing — with the same permissions as the user who asked.Read