SQPrompt / Application-layer protection

Prompts and responses.
Protected in transit.

SQPrompt keeps what people type into AI tools, and the answers that come back, encrypted from their browser or app until it reaches the server you choose.

Your AI model runs unchanged. SQPrompt is delivered as front-end and back-end SDKs and deployed on your infrastructure.

YOUR SESSION → YOUR SERVER SQPrompt
Browser or app Front-end SDK
Encrypted prompts & responses CDN · Firewall · Load balancer
Your backend Back-end SDK
Decrypt at the server you choose. Your existing AI model runs unchanged.
Customer-hosted SDKs Works alongside TLS No keys to manage
The problem

TLS protects the pipe, not the data inside it.

An AI prompt is the sensitive content itself. Much of the path it travels runs through organizations you do not run. Under TLS alone, each intermediary that terminates the connection sees plaintext.

TLS protects the pipe, not the data inside it.

Why today's fixes fall short

Today's fixes leave the payload exposed, or the cost high.

Current security approaches: coverage and remaining exposure
Fix What it covers What it leaves
TLS and certificates The connection between two points Plaintext at every intermediary that terminates it
Session tokens and cookies Proof of who signed in A leaked token stays valid for its remaining lifetime
Content filtering and data-loss scanning What a prompt says The prompt and response in transit between user and server
A key program for the payload The data, end to end Keys to store, distribute and rotate
The difference

Security without the cost of running it.

The usual trade

  • Keys you must manage, distribute and rotate.
  • Security or low operating cost, not both.

With SQPrompt

  • No keys to manage, distribute or rotate.
  • No secret or key is transmitted, only a sync reference.
  • A new transition commits every one to two seconds.
There is still an encryption key. It is never sent, and no one has to manage it.
How it works

Both ends derive their own key material and keep it in step.

One session, start to finish. Sign-in, single sign-on and MFA stay with your own identity layer.

You authenticate the user

Your identity check runs as it does today, unchanged.

Your backend starts a session

It binds the session to the result of your identity check and creates a starting synchronization reference, which it delivers to the front-end SDK.

The front end completes provisioning

The session becomes trusted and unique to that session. Browser and backend now hold synchronized state, and the state commits a new transition every one to two seconds.

Each end derives its own key material

No secret or key is transmitted, only a sync reference.

Prompts and responses move through the channel

Your backend decrypts at the point you choose and forwards the request to your existing AI model, unchanged.

SQPrompt's session material rotates locally every one to two seconds, so a stolen snapshot of it is useful for seconds, not hours.
Where it sits

On top of the TLS you already run.

SQPrompt works at the application layer, independent of TLS and complementary to it.

You choose the trust boundary. Decrypting deeper strengthens it, and leaves less for edge tooling to inspect. Most customers decrypt upstream of their AI gateway or prompt-security tools, so those tools still see plaintext. That is a trade against edge inspection, not a limit of the product.
Where it applies

Built for teams putting AI tools into real use.

Enterprises deploying internal or customer-facing AI tools, regulated industries piloting LLM use cases, and security teams evaluating AI data exposure.

Internal and third-party LLM services

Encrypt prompts and responses between an enterprise session and the LLM service behind it.

The AI tools people already use

Secure customer-support, coding-assistant and copilot tools in the browser, mobile and desktop apps already in place.

Upstream of your AI gateway

Decrypt at a point on the network path ahead of your gateway or prompt-security tooling, so those tools inspect plaintext. This is the recommended configuration.

Sovereign and private AI

For organizations that keep their models and data on their own infrastructure, SQPrompt protects the path prompts and responses travel between the user and that infrastructure.

Built to fit

It fits what you already run.

Your infrastructure

SQPrompt is delivered as front-end and back-end SDKs. Deployed on your infrastructure, it sends no customer data to SQE.

Your identity check stays yours

SQPrompt complements sign-in, single sign-on and MFA. It does not replace them. SQE binds the result of your check to a single-use session.

Your AI model, unchanged

SQPrompt protects the prompts and responses. It does not modify the underlying model.

An honest limit

SQPrompt governs who can establish a session, not who is at the keyboard. Its strength is the strength of your own check.

Questions

What security and platform teams ask.

Does SQE see our data?

No. Deployed on your infrastructure, SQPrompt sends no customer data to SQE.

Does this replace our identity provider?

No. Your identity check stays yours. SQPrompt binds the result of that check to a single-use session.

Why decrypt before the AI gateway?

So the gateway and your prompt-security tools can see plaintext. The deeper you decrypt, the less edge tooling can inspect, and the stronger the trust boundary. Where decryption happens is your decision.

Why not just TLS plus a gateway?

TLS ends at each intermediary that terminates the connection, and each one sees plaintext. A gateway or scanning tool looks at what a prompt says. It does not protect the prompt and response as they travel. SQPrompt keeps them encrypted from the user's session until they reach the server you choose, and it works on top of the TLS you already run.

Does SQE hold FIPS, SOC 2 or ISO certification?

SQE does not hold FIPS 140-3 validation, SOC 2, or ISO certification. The platform is designed to deploy alongside a validated module where one is required, and customer-hosted deployments keep customer data on customer infrastructure.

Start the conversation

Define your trust boundary.
Protect the path to AI.

Talk with SQE about your infrastructure, identity layer, and where SQPrompt fits in your AI deployment.

Julian Quiñones

Board of Advisors

Julian is an accomplished scientist, investor, and entrepreneur with over a decade of experience in biotechnology research and development. His expertise encompasses the full spectrum of R&D, from early discovery to late-stage development, offering a unique blend of scientific insight and strategic business acumen. At SQE, Julian leverages this dynamic perspective to drive innovation and refine our products and services. He holds a degree in Biotechnology from Endicott College and currently serves as a Principal Scientist at Strand Therapeutics.  

Joe Anter

Chief Sales Officer

Joe has over 30 years of leadership experience in emerging technology sales. Notably, he led Proofpoint’s sales team during its IPO, orchestrating strategies that propelled the company forward. This effort culminated in Thomas Bravo’s landmark $12.3 billion software acquisition in 2021, solidifying Proofpoint’s position in the market. Prior to this, he directed a dynamic sales team of over 20 members at Granite Telecom, overseeing operations catering to Fortune 1000 sectors. His leadership played a pivotal role in optimizing sales strategies and fostering strong client relationships, contributing to the company’s growth and success in the competitive telecommunications landscape. At Growgenics, Joe’s transformative leadership as VP of Business Development at Growgenics saw him spearheading the creation of a sales pipeline from scratch, propelling the company from zero revenue to generating multi-million-dollar revenues annually.

Mike Goodwin

Chief Financial & Operating Officer

Mike is an accomplished finance professional with experience in various industries, including working in the Emerging Technologies Division at EMC and Global Finance Analysis team at Boston Consulting Group specializing in detailed financial analysis, developing financial plans, and driving competitor intelligence analysis. Recently as General Manager of Cultivation and Processing at Sanctuary Medicinals, Michael grew and led a team of 100+ across cultivation and production developing effective team structures, standard operating procedures, and streamlining production strategies. Michael holds a Bachelor of Business Administration with a major in Finance and a minor in Information Technology from the Isenberg School of Management at the University of Massachusetts Amherst.

Akram Khalis

Co-Founder

As an entrepreneurial executive, Akram’s background in technology, product, and general management allows him to bridge the gap between engineers and businesses to bring high quality solutions to market efficiently. His diverse knowledge in the development of hardware, firmware, and software. In addition to his vast industry experience, Akram holds a Bachelor of Science in Electrical Engineering from the NJ Institute of Technology and currently holds 5 US technology patents. AK has accelerated the growth of innovative technology for more than a decade.

Rick Genga

Co-Founder

Rick is a highly accomplished entrepreneur and innovator with over 35 years of experience in advanced product development, engineering, software, and business development. His expertise spans innovative areas such as product development, manufacturing systems, business development, electronics, software, and lean design for manufacture. This diverse background has enabled him to lead groundbreaking projects and deliver exceptional value across multiple business sectors in such fields as medical, consumer, industrial, dental, controlled environmental agriculture, and military. Rick has acquired 17 patents throughout his career.

Hamid Pishdadian

Founder/CEO/Chief Architect

Hamid is an award-winning design engineer, inventor and technology executive who holds more than 20 U.S. and international patents for his innovative work. His fields of expertise include computer science, electrical engineering, robotics, artificial intelligence with direct experience in neural networks, genetics algorithms, fuzzy logic, and soft computing. Hamid is familiar with more than 20 high-level and low-level programming languages and has written millions of lines of code in his 35 years of experience as a design engineer. From 1993 to 2000, he worked at Taco Inc., where he designed a genetic algorithm system to automate the design of split capacitor motors. This effort led to the creation of Taco 0013; the most efficient circulator ever designed. In 1997, Hamid won first prize in Microchip Corp international mechatronics competition. In 2006, Hamid invented a 3D camera system that uses genetically optimized neural transformation matrices instead of laser- scanning. His patent for this invention has been referenced by many Fortune 100 Companies. From 2010 to 2019, Hamid served as the Chief Technology Officer of MHT Lighting in New York, during which he earned several patents in the field of high-energy power switching and energy reduction systems. He has been the president of General Sensors, Inc. since 2008 and the Chief Technology Officer of Growgenics since 2019. Hamid is a graduate of the University of Rhode Island, where he received a Bachelor of Science in mechanical engineering. He lives in Warwick, Rhode Island.