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Before Kalepa, underwriters at Paragon Insurance reviewed only about 30% of incoming submissions, with some programs receiving around 50,000 a year. Within 90 days the MGA had its full submission inbox running through Kalepa, extraction accuracy reached roughly 98% to 99%, and its quote-to-bind ratio doubled within a year, according to a case study Kalepa published in March 2026.

Kalepa suits commercial and specialty carriers, MGAs and mutuals whose underwriters cannot read everything that arrives. It covers more of the underwriting chain than most rivals, from intake and clearance through rating and quote documents, while leaving the core policy system in place. Its score would rise with more pricing transparency and outside validation: there are no published plans or public user ratings yet. We rate it 7.4/10 on our scale. We have not used Kalepa ourselves; this review is based on Kalepa’s website, its published case study and news coverage.

One Detailed Case Study and Portfolio-Wide Claims

Kalepa publishes one detailed customer story and a set of portfolio-level claims, plus a funding history that dates back to 2021.

The Paragon story is the most useful item for buyers because it names the customer, the starting point and the timeline. Doubling quote-to-bind is a commercial result, not just an efficiency one: it means underwriters spent their time on business that converts. The 90-day rollout also supports Kalepa’s claim that it goes live in weeks.

The customer list matters too. Berkley, Munich Re and Canopius are large, sophisticated underwriters, and Church Mutual’s 2026 partnership adds a mutual insurer to the mix. That breadth suggests the platform handles different underwriting cultures, from fast-moving E&S programs to more conservative mutual books.

The portfolio-level figures are bigger but come without a method, sample or time frame, so ask a reference customer to confirm them. The last disclosed funding is the 2021 Series A, which is modest next to some rivals’ recent rounds.

Kalepa Modules From Inbox to Binder

Kalepa describes its product as modular, domain-specific AI agents for underwriting. An AI Ensemble Engine picks the right model or method for each task in real time and decides when to automate and when to put the decision in front of an underwriter.

Ingestion and Clearance

Submissions arrive by email and are classified automatically. Kalepa extracts data from hundreds of document types, including ACORD forms, statements of values, loss runs and supplemental applications. Clearance then checks for conflicts with existing submissions, verifies the submission is complete, runs sanctions screening, confirms the producer is appointed and routes the file through a standard or automated path. At Paragon, each submission was processed within minutes.

Kalepa Triage by Likelihood to Bind

Triage ranks submissions by their likelihood to bind and by fit with appetite and guidelines. This is the step that let Paragon move from reviewing about 30% of submissions to working the ones most worth quoting.

Risk Analysis

For each account, Kalepa builds a single view of exposures, controls, terms and broker communications. It enriches the file with third-party data and public information such as news articles, legal filings and public records, and highlights the risk factors that matter most for the line. Paragon’s underwriters use a dashboard snapshot of each risk at the start of the day.

Rating, Quote and Bind

Rating auto-populates rating criteria and compares pricing scenarios. Kalepa works with pricing models in Excel, external raters and internal systems, so carriers keep their own pricing logic. Quote and Bind manages forms and generates quote and binder documents for the underwriter to finalize.

Portfolio Management

At the portfolio level, Kalepa links account decisions to the overall book and makes automated recommendations on product, rate and appetite.

A Day in the Workflow

Put together, the modules change the shape of an underwriter’s day. Instead of opening a shared inbox and picking files by broker or by gut feel, the underwriter starts from a ranked list in which every submission has already been extracted, checked for conflicts and sanctions, confirmed as coming from an appointed producer and scored for appetite. Files that fail clearance have been routed elsewhere. For the accounts worth quoting, the risk summary, third-party research and pre-filled rating inputs are waiting, so the underwriter’s time goes on judgment and broker conversations rather than data entry.

Paragon’s executives describe exactly that shift in the case study: their president of E&S lines singles out triage as the feature he values most, and a senior underwriter points to the per-risk snapshot as the faster way to assess an account.

What Stays With the Underwriter

Underwriters still judge the risk, set the final price and decide whether to bind. Kalepa does the reading, checking, research and paperwork that surrounds those decisions. The 2021 description of its Copilot tool captured the intent: learn from top underwriters’ decisions so others can decide faster and more accurately.

Kalepa Rollout Timeline

Kalepa says the platform works out of the box and connects to existing core systems. Paragon started with the submission inbox and had all of it flowing through Kalepa within 90 days, which is a reasonable planning benchmark for a first line.

How Kalepa Prices Its Platform

Kalepa publishes no price list. This table summarizes what its site shows.

Valuing Kalepa Against Paragon’s Results

Without published figures, buyers should size the deal by the work Kalepa takes on.

• A specialty MGA like Paragon: roughly 20 to 25 programs and tens of thousands of submissions a year. The value case rests on how many of those go unreviewed today and what a higher quote-to-bind ratio is worth in premium.
• A carrier adding only clearance and triage: a narrower first phase keeps cost and risk down; rating and quote modules can follow once accuracy is proven.
• A mutual expanding commercial lines: the portfolio module and risk research help newer lines, but each line needs its own appetite rules and rater connections.

Extra costs to ask about: integration work with your policy system and raters, third-party data sources used for enrichment, and any fees tied to submission volume or premium.

A practical way to judge the price once you have a quote is to work backward from Paragon’s results. If your team reviews a minority of submissions today, estimate the premium you would gain if quote-to-bind improved by even a quarter of what Paragon reported, and compare that to the annual fee. That frames the negotiation around outcomes rather than seats.

Kalepa Compared With Federato, Indico Data, Sixfold and Pibit.AI

These vendors overlap on commercial submissions but cover different stretches of the underwriting chain.

Kalepa’s advantage is breadth without replacing the core: it reaches rating and quote documents while still feeding the policy system you have. Federato goes further into the core, and Indico, Sixfold and Pibit.AI stop earlier in the chain. More options sit on our AI agents for insurance page.

To compare fairly, run a month of real submissions through each shortlisted tool and measure the share processed without manual touch, extraction accuracy and how often triage agrees with your best underwriters.

Kalepa is also the vendor in this group with the most specific public customer story. Federato and Indico Data publish larger aggregate claims, but Paragon’s named executives, timeline and before-and-after figures make Kalepa’s case easier to check through a reference call. Ask every vendor on your list for a comparable reference in your own lines of business.

MGAs With Unread Submissions and E&S Underwriters

• MGAs and specialty carriers with unread submissions: Paragon’s jump from 30% coverage to a full inbox is the use case Kalepa documents best.
• E&S and program underwriters: its published customers sit largely in specialty and excess and surplus lines.
• Insurers keeping their core system: Kalepa connects to existing raters and policy systems instead of replacing them.
• Teams that want rating help: auto-populated rating criteria and scenario comparisons go further than intake-only tools.

Personal Lines Carriers, Claims-First Buyers and Brokers

• Personal lines carriers: Kalepa focuses on commercial and specialty underwriting.
• Claims-first buyers: claims agents such as Shift Claims or Clive by Five Sigma fit better.
• Agencies and brokers: distribution-side tools such as Sonant AI serve agency workflows.
• Buyers who need peer reviews: there are no public ratings on major review sites yet.

Questions to Ask Kalepa

• Portfolio metrics: the 960 basis point, 30% and 58% figures come without methods, and sharing them would help buyers.
• One detailed case study: Paragon’s results are strong, but they come from a single MGA.
• Integration work: connecting to raters, Excel models and policy systems is still a project, even if the platform works out of the box.
• Funding disclosure: the most recent round on record is a 2021 Series A, so ask about the company’s financial runway in a long contract.
• Third-party data: risk research draws on news, legal filings and public records, so confirm how sources are cited in the file and how outdated or wrong records are corrected.
• Automation thresholds: the Ensemble Engine decides when to automate; ask how those thresholds are set and audited.

Kalepa Paragon Study and 2026 Hires

On March 18, 2026, Kalepa published a case study on Paragon Insurance, reporting a doubled quote-to-bind ratio and roughly 98% to 99% accuracy. Its news page lists the appointment of Audrey Howell as head of product in March 2026, a partnership with Church Mutual in September 2026 and the appointment of Garrett Schlesinger as CTO in October 2026, along with Kalepa’s place on FinTech Global’s 2025 AIFinTech100.

Kalepa on Our Scoring Scale

Kalepa scores 7.4/10 on our scale. On product substance it rates well: it handles the whole run from inbox to quote documents, its clearance step includes sanctions and producer checks, and the Paragon case study shows a fast rollout and a commercial result. Autonomy is its strongest criterion.

Published pricing, public user ratings and named integrations would lift the overall score. For specialty carriers and MGAs with submission backlogs, it deserves a pilot measured against Paragon’s numbers. For insurers planning a core replacement, Federato covers more; for teams wanting only intake, Indico Data is lighter.

Before signing, ask Kalepa for a reference customer in your lines, a written description of which steps run automatically and which wait for an underwriter, and the integration plan for your raters and policy system. Set pilot targets on coverage of the inbox, accuracy and quote-to-bind so that the decision to expand rests on your own data.

Specialty Insurer Questions About Kalepa

How Much Does Kalepa Cost?

Kalepa does not publish prices. Insurers book a demo and receive a quote, so ask how cost scales with submission volume, modules and users.

What Results Has Paragon Insurance Seen With Kalepa?

According to Kalepa’s March 2026 case study, Paragon moved its full submission inbox onto Kalepa within 90 days, reached about 98% to 99% accuracy and doubled its quote-to-bind ratio within a year.

Does Kalepa Replace Our Rating Engine?

No. Kalepa auto-populates rating criteria and compares scenarios using your Excel models, external raters or internal systems, so your pricing logic stays in place.

What Is Kalepa Copilot?

Copilot was the name Kalepa used for its underwriting tool when it raised its Series A in 2021. Today the company describes a modular platform of underwriting agents covering ingestion, clearance, triage, risk analysis, rating, quote and bind, and portfolio management.

How Is Kalepa Different From Federato?

Both target commercial underwriting. Kalepa works alongside your existing core system, while Federato also sells policy administration, billing and claims modules as an AI-native core.