Full-scale projects delivering measurable impact across banking, payments, fintech, and wealth management.
Live at one of the world’s largest payments firm
2x
Growth in product uptake
$100M+
Projected annual value creation
1000+
Combinations of products, placements, offers, and actions
The client needed to drive product uptake across customers (merchants). Existing models were not providing enough lift/engagement
Transformers-based Next Best Action engine that analyzes sequential customer interactions, profile, behavioral, and transactions data to surface the right product recommendation at the right moment. The NBA solution learns continuously from customer activity to improve recommendations over time - enabling hyper-personalized customer experience.
Live across three enterprise deployments in financial services and fintech — a proven, IP-backed solution generating recurring impact at scale
60%
Productivity gains for architects and design teams
20%
Productivity gains for software engineers
3 weeks
Time to market
Fragmented workflows across meetings, documentation tools, and architecture platforms create silos, while manual conversion of discussions into structured requirements, repetitive documentation, and lack of end-to-end traceability make the SDLC process time-consuming, error-prone, and difficult to govern.
Created an Agentic AI orchestration layer to interact and track usage of AI tools in the SDLC process. It connects applications across the full SDLC and deploys dedicated AI agents at each stage. The orchestrator works within existing tools- so developers and architects get the full benefit of AI without changing how they work.
Live across multiple enterprise clients in financial services
$1.2M+
Annual cost savings
2 min
Avg response, down from 20+ minutes
65%
Productivity improvement
High volumes of inbound customer correspondence across channels demanded constant manual review, categorization, and routing. The process was time-consuming, inconsistent, and slowing down customer resolution at scale.
An AI-driven solution that streamlines customer correspondence processing workflow by categorizing intents, automating request handling, and generating accurate, SOP-based responses. Agentic AI orchestrates Worker Agents to classify intents, execute actions, and generate responses, all under the guidance of a central Supervisor Agent.
Deployed at one of the world's largest payments firms
+19.4%
AUPR lift vs best ML model
$30M+
Estimated losses avoided
1 Model
Replacing multiple legacy models
The client was building and managing more than 25 ML based models for marketing, decisioning, fraud, collections and more – each with challenges of performance, iterations, engineering, and need for continuous improvements.
We built an event-based foundation model using account, interactions and transaction data with capability to expand to multiple use cases, replacing independent model creation with use case adaptation on FM.
Live in production at one of the large global payments
80%
Productivity gains across the full SAR cycle
Human-in-the-loop
Control preserved for final regulatory submissions
High dependency on manual and subjective workflows for data collection, red flag mapping, analysis, and narrative drafting. Subjective red flag mapping across multiple typologies combined with disconnected internal and external data sources, lead to inconsistent SAR analysis and narratives across investigators.
An Agentic AI solution that automates and standardizes SAR investigation and filing through red flag identification and typology mapping, case file analysis, and compliant SAR narrative generation. Human-in-the-loop validation preserves investigator oversight and accountability throughout the reporting process.