Silver AI is Silverline's enterprise AI agent platform, launched on 2 February 2026. It runs task agents over your existing systems, inside your own perimeter, under approvals and guardrails your people set.
Silver AI platformOn Silver AI an agent is not an open-ended assistant. It is a bounded worker: it has a job description, the connectors it is allowed to use, the approvals it must seek and the record it must leave behind.
Each agent is scoped to one piece of work: review a case, reconcile a ledger, draft a memo, triage an alert. It reads from and writes to core banking, ERP, CRM, ticketing and document stores through governed connectors, using the permissions of the role it acts for.
Longer processes are composed from agents and deterministic steps. The orchestrator tracks state, retries and time-outs, hands work between agents and people, and keeps the whole run visible as one case rather than a chain of disconnected calls.
Approval points are declared per workflow: by action type, monetary threshold, confidence score or customer segment. The approver sees the evidence and the proposed action, and their decision is recorded alongside the agent's.
These are the kinds of agents Silver AI is built to run. Each is a starting configuration; the connectors, policies and approval thresholds are set for the specific institution during the design stage.
Assembles the customer file, checks documents against policy and watch-lists, flags gaps and prepares the case for a named reviewer's sign-off.
Matches ledger, settlement and bank-statement entries, investigates the breaks it can explain and routes the rest with a written rationale.
Drafts the credit appraisal note from financials, bureau data and internal history, in the house format, with every figure traced to its source.
Compiles periodic returns and disclosures from the systems of record, checks them against the schema and prior filings, and stages them for compliance review.
Extracts invoice data, matches it to purchase orders and receipts, applies tax and tolerance rules and posts or holds according to the approval matrix.
Watches shipment, inventory and supplier signals, classifies disruptions by impact and proposes the mitigation the planner should approve.
Correlates telemetry, maintenance history and grid conditions to surface anomalies early and open work orders with the supporting evidence attached.
Enriches alerts with asset and identity context, de-duplicates, scores severity and hands the analyst a case that is already half worked.
A note on scope. The catalogue reflects Silverline's stated AI focus areas of cyber-threat detection, supply-chain resilience and energy and grid optimisation, alongside its financial-services practice. Agents outside these areas are scoped case by case.
The discipline is fixed so that oversight is portable. Once a risk team has reviewed one Silver AI agent, they know how to read the next one.
The agent receives a case, document or event from the system of record. Access is scoped to the role it acts for; nothing is copied outside the environment.
It plans the task against the written policy, retrieves what it needs from approved sources and produces a proposed action with the evidence behind it.
Actions go through governed connectors with allow-lists per agent. Where the policy or confidence threshold requires it, the action waits for a named approver.
The outcome is checked against the expected state and the evaluation suite. Mismatches trigger a retry, an escalation or a roll-back, never a silent pass.
Inputs, reasoning, actions, approvals and timings are written to an immutable log that internal audit and regulators can query without engineering help.
Silver AI is deployed as software inside the customer's environment. Silverline does not operate a shared multi-tenant service for enterprise workloads, and does not use customer data to train models.
Runs in your cloud account or your data centre. Network egress is limited to the model endpoint you approve, or to none at all with a locally hosted model.
Customer data, logs and embeddings stay in the region you choose. Reference deployments keep everything within India to satisfy sectoral residency expectations.
Agents inherit permissions from your identity provider. Who can configure, approve, run and read an agent are four separate rights, each assigned to a role.
Every read, write, approval and model call is logged with its inputs and outputs. The log is append-only, exportable and retained on the schedule your policy sets.
Each agent ships with an evaluation suite built from your historical cases. Promotion to production requires passing agreed thresholds; guardrails block disallowed actions at run time.
Works with the foundation model your organisation has approved, hosted by a provider or on your own infrastructure. Models can be swapped without rebuilding the agent.
Agents are only useful if they can reach the work. Silver AI connects through governed connectors, each with its own allow-list of operations, so that an agent can read a ledger without being able to post to it unless that right has been granted.
Custom connectors. Where a system has no supported connector, one is built during the engagement to the same allow-list and logging standard.
Robotic process automation has a place, and many customers keep it for the fully deterministic steps. The difference shows where the input is unstructured, the path varies, or a judgement has to be recorded.
| Dimension | Traditional RPA | Silver AI agents |
|---|---|---|
| Input | Structured fields and fixed screen positions | Documents, messages, records and events, structured or not |
| Process variation | Breaks when the path or the interface changes | Plans each case against policy; exceptions are handled, not dropped |
| Judgement | None; every branch is scripted in advance | Bounded reasoning with the rationale recorded for review |
| Human involvement | Manual hand-off outside the tool | Approval points declared in the workflow and logged with the outcome |
| Evidence | Execution logs | Inputs, reasoning, actions, approvals and model calls in one audit record |
| Change control | Re-script on each system change | Re-run the evaluation suite; connectors absorb most interface changes |
| Best suited to | FixedHigh volume steps with no ambiguity | VariableDocument-heavy work that currently needs a person to read and decide |
Tell us the process, the systems involved and the controls you would need. We will show you what an agent for it looks like, including the audit record it leaves behind.