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Obin AI

Also known as: Obin

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Enterprise operations agentindependentVerified 2026-07-08

Agentic AI workforce for financial institutions that runs origination, underwriting, monitoring, and fraud workflows end to end with regulatory grade auditability and institutional memory.

Obin AI builds an agentic workforce for financial institutions, deploying domain specific AI workers that run defined workflows end to end inside a firm's controls and audit boundaries across banking, insurance, and asset management, with an initial wedge in private credit. Rather than copilots that assist at the task level and require a human at every step, Obin's agents own workflows: in origination and diligence they extract deal terms and financials from documents, pre populate LBO models, run real time economics such as ROA, IRR, and MOIC, identify comparable structures from a fund's history, and draft investment committee ready memos; in monitoring they track covenant compliance and portfolio performance continuously and flag deterioration only when risk signals converge; and in banking they pre populate risk scorecards, assemble approval packages with audit trails, and detect fraud in real time while reducing false positives. The system is model agnostic and evaluation driven, built for the near perfect accuracy, auditability, and regulatory alignment that capital decisions demand, where 95 percent correct can be 100 percent wrong. An open architecture lets institutions retain full ownership of their models, data, and IP rather than handing them to a closed ecosystem, and the agent layer embeds decades of institutional context so firm specific logic and knowledge compound and persist even as people rotate off teams. In production it has processed more than 50,000 annual loan notices for a private credit fund with over $500B, saving most of the manual time.

Vendor details

Canonical URL

https://www.obin.ai

Category

Enterprise operations agent

Funding status

Seed of $7M led by Motive Partners (emerged from stealth March 18, 2026), with angel investors and advisors Dr. Fei-Fei Li and Lukasz Kaiser. New York based. Co-founders Apoorv Saxena (CEO, former Head of AI at JPMorgan; led Google Cloud AI products including Translate and Contact Center AI) and Valliappa Lakshmanan (CTO, former Google and Silver Lake, author of several AI books). Clients reportedly represent over $1T in assets under management, including a top-five U.S. bank and Pinegrove.

Company status

independent

Use cases & customers

Primary use cases

credit analysis and underwritingdeal origination and due diligenceportfolio and covenant monitoringfraud detectioninvestment memo generation

Target customers

banksasset managersprivate credit fundsinsurersfinancial institutions

Deployment options

SaaScustomer-controlled (open architecture)in-environment

Integrations

Deploys AI workers directly inside a firm's existing workflows, controls, and audit boundaries under an open, no lock in architecture, ingesting legacy documents, CIMs, and multi decade unstructured records. Specific connectors were not enumerated on the retrieved pages.

Capability coverage

12.0 / 14 capabilities · 86%

Integrations & Tool CallingDeploys AI workers directly inside a firm's existing workflows under an open, no lock in architecture and ingests legacy documents, CIMs, and multi decade unstructured records, though specific integration connectors were not enumerated on the retrieved pages. Full
Workflow OrchestrationAgents run defined financial workflows end to end, for example origination and diligence (extract terms, pre populate models, run economics, draft IC memos), continuous portfolio monitoring, and approval package assembly, with humans supervising rather than managing each step. Full
Knowledge Grounding & RAGThe agent layer embeds decades of institutional context and reasons across multi decade datasets, legacy documents, and unstructured records with inference and cross referencing beyond simple extraction, grounding outputs in firm specific knowledge and policies. Full
Human Oversight & GuardrailsObin frames AI as augmenting not replacing people: humans supervise rather than manage each step, agents run within the firm's controls, audit boundaries, and governance standards, and outputs preserve human judgment for high stakes capital decisions. Full
Security, Identity & GovernanceBuilt for regulated environments with every interaction auditable, traceable, and aligned to internal governance, and an open architecture in which institutions retain full ownership and control of their models, data, and IP rather than handing them to a closed ecosystem. Specific certifications were not retrieved. Full
Observability & AuditabilityEvery interaction is auditable, traceable, and inspectable, producing regulatory grade audit trails, and agents assemble approval packages with audit trails so outputs can be relied on in mission critical financial workflows. Full
Memory & State PersistenceInstitutional knowledge compounds and persists even when people rotate off teams: the agent layer codifies investment decision making from past deals and retains firm specific logic and multi decade context as durable institutional memory. Full
Deployment & Data ResidencyAn open, no lock in architecture keeps institutions in full ownership and control of their models, data, and IP rather than handing data to a closed ecosystem, with agents running inside the firm's own controls and boundaries, providing strong data sovereignty. Full
Prebuilt Agents / Templates / PacksProvides prebuilt, domain specific financial workers across credit analysis, origination, underwriting, portfolio monitoring, fraud, and claims, but these are configured per institution rather than offered as a self serve catalog of templates or packs. Partial
Triggers & Channel CoverageExecution is continuous rather than episodic: agents monitor covenant compliance and portfolio performance in real time, detect fraud in real time, and flag deterioration only when risk signals converge, driving event based action across financial workflows. Full
Model Flexibility & RoutingObin describes a model agnostic, evaluation driven agentic system, and its open architecture lets institutions retain control over the models used, indicating flexibility across underlying models. Full
APIs / SDKs / MCP ExtensibilityThe open, no lock in architecture is built to integrate with a firm's existing systems, but no public API, SDK, or MCP surface for building on Obin is documented on the retrieved pages. Partial
Testing, Debugging & OptimizationObin describes an evaluation driven agentic system that earns reliance through evaluation backed performance and long tail reliability, bridging baseline agentic outputs to production grade accuracy for high stakes workflows. Full
Browser / Computer-useObin operates over financial documents, data, and workflows. No browser automation or general computer use capability is documented. Unable to verify

Recent platform changes

No recent material changes tracked yet.

Pricing

Contact sales; no public pricing. Enterprise, outcome oriented for financial institutions.

not disclosed; enterprise engagement

Contact onlyMedium variable cost

Cost watchouts

Implementation involves encoding institution specific logic and integrating with regulated workflows; cost is scoped per deployment and workflow rather than a public rate.

Variable cost rationale

Enterprise platform scoped by workflows and volume; no public rate card, so exposure is moderate and not precisely determinable, though outcome oriented pricing may tie cost to measurable results.

Sales call required

Yes — required for paid access

Free / trial

No public free tier; enterprise pilot to production

Lowest paid plan

Not public

Key ambiguities

No public pricing. Whether billing is per workflow, per seat, or per outcome is not disclosed.

Verified 2026-07-08

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