Pillar01
Agent Studio
Build, configure, test, publish, embed and observe your own governed AI agents — without writing code. Capabilities, tools, guardrails, and the surfaces they answer on are all controlled through one Studio your team owns.
The Agentic AI Operating Model · For Regulated Finance
Build · Govern · Audit your AI workforce
Ship more modelswith agentic AI.
You modelled the PD in two weeks. The MRD, validator pack and SR 11-7 trail took two months. Sovaryn runs the model lifecycle as a workforce of governed AI agents — drafting documentation, gathering validator evidence, triaging drift, defending the decision — so your team spends its week shipping the next model, not maintaining the last one.
The Problem Section
The work around the model is now the bottleneck.
The model risk function was invented for an era when a bank shipped four models a year. Today the same team is asked to govern forty — each with its own data lineage, fairness profile, and regulator-facing narrative. The tooling never caught up. So data scientists hand-write MRDs in Word. Validators hand-collect evidence from Slack. Risk officers reconcile capital impact in Excel.3
The cost is not the documentation. It is the modelling that doesn’t happen — the credit policy never rebuilt, the AML feature never tested, the fairness audit never closed — because the team is too busy defending the last model to build the next one.
“We rewrote the same MRD three times in 2024 because the policy template kept changing. That’s 600 person-hours we should have spent on the new SME-PD model.”
— Senior validator, top-5 Indian private bank
Sovaryn was built so the work around the model handles itself — a workforce of governed AI agents that draft documentation, gather validator evidence, triage drift and assemble regulator packs in the background, while your team builds the next model. Every reviewer, every regulator, and every CRO sees the same evidence trail in the same place. Not someday. Today.
3 Sovaryn pilot data, anonymised across six lending and three insurance institutions, FY23–FY24. Methodology available on request via Compliance Desk.
The Platform
An operating model, not a workflow.
Sovaryn is not another GRC tool, and it is not a chat assistant. It is a workforce of governed AI agents that runs the model-lifecycle itself — from the moment a charter is registered to the day a regulator asks why the model declined on 14 March.
Sixteen agents ship out of the box. A no-code Studio lets your team build the rest. Every agent runs through one Cascade — versioned, gated, human-checkpointed — so the speed of AI never outruns the speed of audit.
“The first AI platform built around the validator’s decision, not the data scientist’s notebook.”
— Internal product principle, Sovaryn Engineering
Pillar02
Agent Library
Sixteen pre-built agents shipped on day one: MRD authoring, drift triage, validator pack, fairness audit, override review, deployment readiness, regulator response, shadow-AI discovery and more. Clone, configure, deploy.
Pillar03
Cascade Runtime
Every agent runs through Sovaryn’s deterministic seven-stage cascade — versioned, gated, human-checkpointed. There is no “skip” button, even for the administrator. Every artefact carries the previous stage’s real output.
Pillar04
Audit Spine
Every agent action is grounded in a real artefact, signed by a real reviewer, and replayable as one expiring URL. Cited to SR 11-7, RBI MD-ITG, EU AI Act, DPDP. Maker-checker enforced. Overrides permanent.
The Workforce
Sixteen agents on day one. A studio for the rest.
Every Sovaryn agent ships pre-wired to the cascade — versioned, gated, replayable. Configure one in minutes. Build your own in an afternoon.
The Agent Library
— twelve of sixteen shown —
Documentation01
MRD Author
Auto-drafts the Model Risk Document from real artefacts. Cited to the home regime.
Validation02
Validator
Assembles the decision pack — stability, fairness, leakage, lineage, override history.
Monitoring03
Drift Forensics
Triages drift in 90 seconds; commits to one of four typed RCA verdicts with owners.
Compliance04
Fairness Audit
Runs the protected-group panel; emits a number, not a recommendation. Threshold gated.
Governance05
Override Reviewer
Inspects manual overrides daily; surfaces concentration, repeat-reviewer and policy drift.
Release06
Deployment Readiness
Pre-checks all stage-gates before promotion. Fail-closed by default.
Defence07
Regulator Response
Compiles a replayable evidence pack for any past timestamp; emits one expiring URL.
Discovery08
Shadow-AI Discovery
Scans pipelines for unregistered models, retroactively governs them and assigns owners.
Validation09
Backtest Runner
Re-runs historical decisions on revised features; quantifies the swing in approval/loss.
Risk10
Risk Memo Author
Drafts a CRO-ready memo from monitoring deltas and override flags — every fact cited.
Platform11
Cascade Orchestrator
Runs the seven-stage pipeline end-to-end; gates by floor, regime and reviewer.
Operations12
Monitoring Triage
Clusters alerts, dedupes by root cause, routes to the right desk — at 2 a.m. or 2 p.m.
Agent Studio
Build your own agents.
No code. No exceptions.
Studio is where your team turns a recurring operations problem into a governed agent — a fairness audit for credit cards, a backtest for IRB swings, a memo from this week’s overrides. Pick capabilities. Set guardrails. Approve. Ship.
Every Studio agent inherits the same audit spine as the pre-built library: cited artefacts, maker-checker approvals, replayable runs, signed share-links. Nothing escapes the cascade.
Step01
Start from blank or a template
Choose from sixteen pre-built templates — MRD, validator, drift, fairness — or open a blank canvas.
Step02
Pick capabilities and tools
Compose from a governed allowlist: SHAP, fairness panels, RCA verdicts, ticketing, governance comments, owner notifications.
Step03
Set guardrails and triggers
Define floor thresholds, RBAC scopes, cron schedules and signed webhook bindings — all in plain forms.
Step04
Test, approve, embed
Multi-turn chat to test the agent. A human reviewer approves. Embed into any Sovaryn surface or your own.
The Principles
What separates a Sovaryn agent from a generic LLM.
Three architectural commitments. Each one chosen specifically because the market sells the opposite.
01
Every agent shows its work
Each agent action carries the artefact, the citation, and a typed verdict. No paragraph, no paraphrase, no rounded percentage. The validator and the regulator see the same numbers the data scientist saw.
02
Agents that gate, not narrate
A drift agent commits to one of four canonical RCA buckets — population shift, data quality, custom implementation, model design — with the owner team attached. A fairness agent emits a number, not a recommendation.
03
Two reviewers. Zero conflation.
Business and Regulatory reviews live in separate columns of the same drawer. A model that is commercially fine can still fail the regulatory column — and vice versa. Two reviewers, two sign-offs, every override permanent.
Inside the Workbench
Three surfaces, one auditable trail.
A control plane that hints, then proves. Each surface is a complete experience — you only see the depth when you need to.
Fig. 01
The Pre-Model Workbench
Catch the risk before the build.
Leakage, target drift, weak features, fairness exposure — surfaced before training. Stage-wise floors set by the CRO, not a slide. Numbers go to two decimals; verdicts are typed, not narrated.
- —NULL & outlier spike detection vs the registered baseline
- —Schema-drift catch within 200ms
- —Per-feature severity grade (clean / warn / fail)
Fig. 02
The Cascade Pipeline
Seven stages, one deterministic flow.
Inception → Data → Build → Document → Validate → Deploy → Monitor, orchestrated as a single audited trail. Maker-checker enforced. Every signature chained, every override permanent, every fail-closed.
- —Explainability agent wired into Build
- —Documentation agent grounded in real artefacts
- —Validation review created — never auto-approved
Fig. 03
The Defence Layer
Defend any decision, on demand.
Replay any past timestamp. Quote portfolio expected loss in INR. Share an audit view via a single expiring URL — no login, no email thread, no panic. The platform remembers, so your team doesn’t have to.
- —Structured RCA verdicts (4 canonical buckets)
- —Expiring share-links with full state replay
- —Side-by-side autopilot vs human override records
The Cascade
One pipeline. Seven gates. Fail-closed by default.
Each stage is anchored in a real output from the previous stage. There is no ‘skip’ button, even for the administrator.
No.StageSurfaceWhat happens here
01InceptionCharterTier scoring, business case, intake.
02DataPre-ModelDataset fitness, profile, lineage.
03BuildArtefact+ExplainArtefacts, features, explainability artefacts.
04DocumentMRDAuto-drafted MRD with real citations.
05ValidateGateDoc completeness, fairness, floor check, HoMR.
06DeployPromotionRegulatory gate, signed approval, release.
07MonitorLiveDrift, fairness, backtest, alerts, RCA.
Every transition is captured in an immutable audit trail (model_lifecycle_transitions).
From the Field
Four desks. Four problems. Four results.
Composite case studies drawn from active BFSI engagements. Names withheld; methodology available on request.
Credit Risk Desk
NBFC · PD
A PD model, validated in nine days.
A mid-cap NBFC built a fresh applicant PD model on a 14-month sample. Sovaryn cascaded explainability, drafted the MRD against RBI MD-ITG, and queued the validator pack — a process that ran 11 weeks the previous quarter — in nine business days.
AML Desk
BFSI · AML
Shadow AML rules, found and re-governed.
Sovaryn’s discovery scan picked up four rule sets running unaudited on the AML pipeline. Each was retroactively registered, the data lineage reconstructed, and a remediation plan auto-routed to the BSA officer. Two of the four were quietly retired.
Capital Risk Desk
Tier-1 bank · LGD
₹4.2 cr in capital buffer, recovered.
A retail LGD model drifted on month-end. The RCA verdict came back as data_quality — a renamed column in the collections feed. Sovaryn opened the data eng ticket within 90 seconds; the buffer release went out the same day.
Validation Desk
Insurer · IRDAI
A six-week queue, cleared in eleven days.
A validator inherited 47 open reviews. With Sovaryn’s pre-validated decision packs — stability, fairness, leakage, lineage — the queue closed in eleven days. Two of the 47 found genuine model-risk issues; both were escalated and rebuilt.
By the Numbers
What an agentic workforce changes.
Pre-deployment baselines aggregated across seven BFSI design partners. Methodology on request.
73%
less time on MRDs
auto-drafted, cited, signed-ready
5.4×
faster validator throughput
pre-validated evidence packs
92%
audit-ready in < 1 week
across SR 11-7 / RBI / IRDAI
8
shadow models / tenant
discovered in the first week
Metric
Before
After Sovaryn
Time to deploy a model
90–180 days
21–35 days
Time to deploy a model
Before90–180 days
After21–35 days
Audit-pack response
6–9 months
< 1 week
Audit-pack response
Before6–9 months
After< 1 week
Validator throughput
1×
3–5×
Validator throughput
Before1×
After3–5×
Drift incidents detected
Post-impact
Pre-impact
Drift incidents detected
BeforePost-impact
AfterPre-impact
Override visibility
Spreadsheets
100% audited
Override visibility
BeforeSpreadsheets
After100% audited
Documentation effort
6–8 weeks
2–3 days
Documentation effort
Before6–8 weeks
After2–3 days
Aggregated baselines · Q3 2025 – Q1 2026 · anonymised
Compliance
Mapped to the frameworks your supervisor cares about.
Every clause is wired to a working control in the workbench — with audit-log evidence inline.
SR 11-7
Federal Reserve
RBI · MD-ITG
India · BFSI
SEBI · IRDAI
India · Capital + Insurance
DPDP 2023
India · Privacy
Basel III
Global · Capital
EU AI Act
EU · High-risk
ISO 42001
AI management
BCBS 239
Risk data
Subscription
Priced on what reaches production.
Every plan ships the full lifecycle. You only scale price as you scale model count.
Pilot
Freefor 15 days
Run one full cascade end-to-end on your data.
- —One governed model
- —Full lifecycle access
- —Email support
Recommended
Growth
$2,500/ month
10–50 governed models per quarter, with a defence layer.
- —Up to 50 models
- —Time-travel + RAG Copilot
- —Slack + email + webhooks
Enterprise
Customannual
Multi-region, SI-led, audit-grade.
- —Unlimited models
- —SSO + SCIM + BYO cloud
- —24×7 incident support
Full capability matrix available on request · Compliance Desk
Editorial Note
Your AI workforce
should already be working.
Run one full Cascade on one of your models with Sovaryn’s agentic workforce. Fifteen days, no credit card, no commercial conversation. If it doesn’t hold up, you walk away with a free audit-grade evidence pack for the model you tested.
Pilot scope
- 01One full Cascade run on one of your models
- 02Auto-drafted MRD against your home regime (SR 11-7 / RBI / EU AI Act)
- 03A validator decision pack signed by your team or ours
- 04A free expiring share-link your supervisor can audit
No credit card · SOC 2 in flight