An AI workforce, already on your payroll.
Every agent is hired like a person — a job description, a supervisor, a record of everything it does. Symplycyty runs production agentic AI inside your bank's own stack: three suites, over 200 use cases, live in four Tier‑1 banks today.
Live at
Largest private sector bank in India | Largest Islamic bank in the Middle East
174Agents live &
billing — not pilots
billing — not pilots
4Tier‑1 banks in
production
production
270Use cases across
the catalogue
the catalogue
22Languages handled
in production
in production
83People — 70%
product & engineering
product & engineering
The product
Three suites, mapped to how a
01 · Operations Management
123 use cases
Run the regulated back‑office.
Repetitive, regulated work off people's desks — maker‑checker at every gate.
Buyer · COO, Head of Operations
02 · Data Management
57 use cases
Make enterprise data usable.
Turn enterprise data into a governed, queryable asset with zero PII exposure.
Buyer · CDO, CDAO, CIO
03 · Customer Experience & Value
90 use cases
Grow customer value.
Convert existing transaction data into measurable, real‑time growth.
Buyer · CMO, Head of Retail, Cards
Three suites, mapped to how a
bank actually runs.
Not a chatbot bolted on top — agents organised the way a bank is organised, each suite built for the person who owns that budget.
Deployed full‑stack or API‑only — no rip‑and‑replace.
Proof, not promises
What's already running, today.
Four solutions, four different banks, each measured against a control — not a demo environment.
Live at a mid‑size Indian bank
Reads, verifies and routes every regulatory notice,
Reads, verifies and routes every regulatory notice,
end to end.
A mandatory human‑approval gate before any outbound action, with an authenticity
score on every notice.
30sReceived → classified & routed
22Languages handled
88%Ground‑truth accuracy
100%Outbound actions human‑gated
Largest Islamic bank in the Middle East
Continuous monitoring of 100% of transactions —
Continuous monitoring of 100% of transactions —
not a 2–5% sample.
Manual control effort cut by roughly 80%; exceptions routed to the right owner with evidence attached.
3M+Transactions monitored daily
1.2M+Reconciliations per day
<60sBreach to alert
4,200+Man‑hours recovered / month
Largest Islamic bank in the Middle East
Ask the data anything, in plain English.
Sourced answers, charts and insight — no analyst, no SQL — on the bank's own infrastructure,
behind a deterministic plan checker.
$300KAnnual analyst cost saved
500+Daily users
200+Live metrics
0Writes ever generated
Live at largest Indian bank & Islamic bank in the Middle East
One of the largest deployments of AI‑driven offer
One of the largest deployments of AI‑driven offer
intelligence in Asia.
A recommender and enrichment stack over customer genomes and merchant propensities,
measured against a control group.
156MCard transactions analysed / month
65M+Customer genomes scored
$600M+Incremental spend enabled
<1.5sRanked decision returned
What regulated buyers test for
Built to pass the six tests banks now set.
Every regulated buyer runs the same checklist before an agent touches production.
This is what we're built against.
Do the work
Go beyond demos, to production.
Prove the ROI in a quarter
A business case, like any hiring decision — not an innovation budget line.
Know my business
The domain, the data models, the workflows.
Run where I choose
Data stays in your walls, in a VPC of your choice.
Survive your disappearance
Keeps working even if a frontier LLM can't be reached.
Watch it continuously
Monitored so models don't hallucinate or drift.
How we start
A pilot small enough to approve from opex.
No year‑long transformation programme. One entry point, one hero agent, a result you can measure before you commit further.
01 · Land
One agent, one clear job, a pilot sized for opex approval.
Live in weeks, in your own environment, against a use case your team already feels.
02 · Prove
Measured against a control group, not a demo.
The same discipline you'd apply to any hire — a result before the next conversation.
03 · Expand
Pull‑through, not push — your team asks for the next one.
Every deployed agent creates the trust and data that make the next agent an obvious step.
Get in touch
The workforce is the proof. The platform is the asset.
If your team is weighing a pilot for the next two quarters, we'd rather show you what's already live than send a deck.
Suresh Shankar
Founder & CEO
linkedin.com/in/sureshshankar
Siva Shankar Ganesan
President
linkedin.com/in/sivashankarganesan