Your live book, connected to every rail, bureau and partner it depends on.
Lokta's agents work on your live book after approval, held on Lokta's own Loan Ledger and Accounting Ledger. They run inside the cloud you choose or your own private network, on the AI models you approve, connected to the rails, banks, bureaus and partners the book already depends on. An existing book moves across through a reconciled migration. And every connection is proven safe before it can touch the book.
Every connection is a governed integration layer: each feed is risk-rated and proven safe in a controlled path before it writes anything to your live book.
Forty-five minutes. We show how each of your rails, bureaus and partner feeds gets proven safe before it touches your book. Your setup, your questions.
Separate the API from a tested connection
| Status | What it covers | What to verify |
|---|---|---|
| Available now | The published Lokta API surface and current Loan Management capability | Endpoint scope, authentication, version and required permissions in the API reference |
| Deployment-specific | Migration of a book from an existing loan management system; connections to a payment provider, bank, bureau, accounting system or communication channel; cloud and model choices | Named provider, supported version, data direction, residency, owner, error handling and signed acceptance |
| Planned (roadmap) | A requested connector that has not been delivered and accepted for your scope | Written scope, dependencies and acceptance criteria |
Logos do not establish a prebuilt connector, partnership or live deployment. Ask for the status of each named connection. Inspect the current API reference. Staff can also ask Claude about the book, read-only, through the Lokta MCP server.
Every vendor's integration slide is a wall of logos. None of them tell you what happens the first time a bad feed writes to your live book. Lokta's answer is a gate: no connection touches the book until it's risk-rated and proven safe. The logos are the easy part.
Where lending integration projects actually stall.
Buying software is easy. Connecting it to a live loan book, safely, is where the months go and the deals stall. Three fears, and every one of them is fair: lock-in, data residency, and the unsafe write.
Adopting a platform can mean adopting its cloud and its model as well, a one-way door your board has to defend. For an RBI-regulated lender, where the data lives is a requirement rather than a preference: if a borrower's record leaves your boundary, the answer to the examiner is already wrong. And an unrated connector can post a bad settlement straight to the ledger, corrupting the book quietly instead of failing loudly.
This page is the answer to all three: your cloud, your model, your data inside your boundary, and a gate that proves every feed safe before it writes.
Bring the book across. Reconcile it first.
The workforce acts on the book held in Lokta's own agent-native core: the Loan Ledger and the Accounting Ledger. A book on Apache Fineract or any other loan management system (the system of record that holds a live loan: its schedule, dues and history) moves across through a migration, with accounts and balances mapped and checked while the current system keeps running, then cut over.
- Apache Fineract
- Any other loan management system
The guardrail. Every migrated balance is reconciled against the current system before cutover. After it, every read and write is an event on the record: what changed, why, and the policy that allowed it.
Your cloud. Your models. Your data, where the regulator needs it.
Run the workforce on a hyperscaler (the large public-cloud providers) or on-prem, inside your own VPC (virtual private cloud, a private, isolated slice of a cloud that only you can reach). On-prem and VPC are the data-residency answer for RBI-regulated lenders: the book, the models and the record stay inside your boundary, and nothing regulated leaves it. That is a claim a security review can verify for itself, without taking our word for it.
- AWS
- Microsoft Azure
- Google Cloud
- On-prem / your VPC
- OpenAI
- Anthropic
- Google Gemini
- Meta Llama
- Mistral
- Cohere
- + open models
The guardrail. Which model drafts a proposal doesn't change what it's allowed to do. Every action is still scoped to a permission, checked against your policy, logged as evidence and reversible. The governance sits above the model as an independent layer. Change the model and the guardrails stay exactly where they are.
The rails, banks, bureaus and partners the book already depends on.
A live loan runs through more than a core. The workforce connects to the rest of the stack it depends on, payment rails (NACH, UPI and the aggregators in front of them), core banking and the escrow account (a joint holding account that keeps two lenders' funds from mingling), credit bureaus (the agencies that hold a borrower's repayment history), co-lending partners, collection agencies working inside the same policy and the same record, and the borrower's own channels.
- NACH / UPI
- Payment aggregators
- Core banking / escrow
- Credit bureaus
- Co-lending partners
- Collection agencies
- WhatsApp & channels
The guardrail. Every write to a rail, a bureau or a partner is an event on the add-only record, timestamped, attributable, reversible. History is appended, never overwritten.
Every connection is proven safe before it touches the book.
Connect is the layer that stands between your ecosystem and your book. Every feed (a settlement file, a bureau pull, a bank posting, a partner's batch) is risk-rated and proven safe in a controlled path before it can write anything live.A new connection goes live on evidence.
Because every write is an add-only event, a bad feed can be traced, contained and reversed. It cannot quietly corrupt the book. That distinction, proven safe against simply plugged in, is what a security review actually tests for.
Our team built Apache Fineract, the open-source lending core running in production across banks, NBFCs and fintechs. That's why we know what a migration has to carry across from another core: schedules, appropriations, day-count, DPD (days past due), co-lending. It's also why we treat every integration as something to prove safe, not just something to plug in. We've spent a decade inside lending cores; we know exactly how a bad feed breaks a book, so we built the gate that stops it.
What a security review asks first
Migration, clouds, models, and what stops a bad feed reaching the book.
Does Lokta replace our existing loan management system?
Yes, for each book you bring. The agents work on the book held in Lokta’s Loan Ledger and Accounting Ledger, so a book on Apache Fineract or another loan management system moves across through a migration: accounts and balances mapped, reconciled while the current system keeps running, then cut over. You can start with one book, and the agents and the guardrails behave the same on every book after it.
Can Lokta run on-premise or inside our own VPC?
Yes. Lokta runs on AWS, Microsoft Azure or Google Cloud, on-premise, or inside your own virtual private cloud. On-premise and VPC are the data-residency answer for RBI-regulated lenders: the book, the models and the record stay inside your boundary, and a security review can verify that for itself.
Which AI models does Lokta work with?
OpenAI, Anthropic, Google Gemini, Meta Llama, Mistral and Cohere, plus open models you host yourself. The governance is an independent layer sitting above the model, so which model drafts a proposal does not change what the proposal is allowed to do. Change the model and the guardrails stay where they are.
What stops a bad integration from corrupting the live book?
Connect, the safety gate. Every feed, whether a settlement file, a bureau pull, a bank posting or a partner batch, is risk-rated and proven safe in a controlled path before it can write anything live. Because every write is an add-only event, a bad feed can be traced, contained and reversed rather than quietly corrupting balances.
What systems does Lokta connect to around the book?
Payment rails, core banking, escrow, bureaus, co-lending partners, collection agencies and borrower channels are integration categories to scope. Each named provider connection needs mappings, ownership, testing and acceptance; the category list is not proof of a prebuilt connector.
Are the provider logos on this page partnerships?
No. Provider names identify deployment-specific options to evaluate, not confirmed prebuilt connectors, endorsements, commercial partnerships or live customer deployments. Ask for the named version, integration owner and acceptance evidence.
We will run the servicing agents and the integration layer on the cloud and model you name, show how a book from your current system moves onto our ledgers, and map exactly how each of your rails, bureau and partner feeds would be proven safe before it touches your book. Your setup, your questions, forty-five minutes.
Forty-five minutes. contact@lokta.ai · your own stack
Not ready for the session? Check our integration thinking against your own.