Zero-Trust Architecture
Enterprise AI Security
AI introduces entirely new attack vectors. We build semantic firewalls, data redaction layers, and strict access controls to protect your proprietary data from the ground up.
Prompt Injection Defense
If an attacker uses a jailbreak prompt, an unprotected model can leak hidden context. We add semantic guardrails that detect and block adversarial instructions before they execute.
What we could ship with this
Red-team audit
Adversarial testing against jailbreaks, data exfiltration, and tool-abuse for your specific stack.
Hardening playbook
Per-vulnerability remediation with code, config, and prompt changes — not just a list of CVEs.
Penetration test report
EU AI Act / SOC2-aligned report. Use it for auditors, customers, or insurance.
Why AI Needs a Filter
If a model produces malicious markup and your site renders it blindly, the browser executes the attack. We sanitize AI output before it reaches the screen.
What we could ship with this
Output validation pipeline
Fact-check + policy filter between model and user — every response audited and logged.
Hallucination guard
Detects unsupported claims and blocks/escalates them before reaching the user.
PII redaction layer
Strips PII from outputs and logs at egress — never leaks to third parties or analytics.
Enterprise Privacy Guardrails
Never leak trade secrets or PII to public models. Our proxy extracts sensitive data into a secure local vault and sends anonymized placeholders to the cloud.
What we could ship with this
On-prem deployment
Your AI runs in your VPC or air-gapped infra. Sensitive data never leaves your perimeter.
GDPR compliance audit
Right-to-be-forgotten, data-residency, lawful basis — documented for the regulator.
Differential privacy training
Train models that can't memorize individual records — proven mathematically.
Data Governance
Enterprise RBAC Integration
An internal AI should not expose executive data to entry-level employees. We connect models to your identity provider and enforce document-level access control.
What we could ship with this
Per-user RAG ACL
Retrieved chunks filtered by user permissions — sales sees CRM, ops sees ops, neither sees finance.
Tool permission model
Each agent declares which tools it can call; enforcement at the boundary, audited at runtime.
Multi-tenant isolation
Tenant A's data never reaches tenant B's prompt — verified with red-team tests.
Output Validation
Automated Fact-Checking
LLMs hallucinate. We build verification layers that cross-reference claims against trusted systems and correct errors before users ever see the output.
What we could ship with this
Citation enforcement
Every factual claim traced back to a source doc; uncited claims blocked at output time.
Domain-grounded chain
Model can only state facts contained in your docs — anything else returns 'I don't know'.
Compliance audit trail
Every output logged with sources, model version, prompt — replayable for regulators.
Client testimonials
“The prompt-injection red-team audit uncovered 9 critical vulnerabilities our own team missed. We also got MDR-ready documentation.”
S. Péter
Security Lead, healthtech
“The PII redaction layer and RBAC pattern have been issue-free since launch. Exactly what you'd expect for a banking AI system.”
B. Luca
CISO, financial services
What we can build with this
Security audits and hardening you could ship
Adversarial testing and defenses we deliver as a product.
Prompt-injection audit
Red-team your AI systems against jailbreaks, data exfiltration, and tool-abuse attacks.
RAG access control
Per-user permissions on retrieved documents — users see only what they're allowed to see.
Data-leakage scan
Check whether your AI is leaking PII, secrets, or training data through outputs.
Output validation pipeline
Fact-checking and policy filters between the model and your users — every response audited.
Jailbreak defense
Layered guardrails (prompt + model + output) tuned to block attacks specific to your use case.
AI compliance audit
EU AI Act, GDPR, sector-specific compliance review — with remediations and documentation.
Engagement tiers
Four ways to put senior AI engineering inside your business
Fixed prices. 100% IP yours. Most clients start with a 30-min scoping call so we agree on the right tier before any building.
Projects by us
AI projects we built
AI systems built by us — same stack we ship to clients.
aiwebmobile
AIHealthIQ
AI health coach powered by wearable data
Ingests wearable data (heart rate, sleep, steps, oxygen) from watches and fitness bands, correlates it with AI, and surfaces concrete lifestyle, medication, or 'see a doctor' recommendations. Web and mobile clients on the same API.
Stack
ExpressReact-ReduxSQLiteOpenRouter
aiweb
3D AI Property
AI that turns flat specs into a walk-through 3D interior
Type a flat's specs and the AI generates its 3D floor plan + interior, which you can fine-tune by hand and walk through in FPV or drone view. Swap between ten interior styles in one click — no interior designer needed.
Stack
Next.jsTypeScriptOpenRouterSQLite
aiweb
The Truth AI News
Fact-checked news aggregator with AI bias scoring
News aggregator that pulls from multiple sources, fact-checks with AI, summarises the piece, and scores how biased / opinionated it is plus what the article is trying to achieve. Editorial transparency is the whole point.
Stack
Next.jsTypeScriptPrismaPostgreSQLOpenRouter
aiblockchain
Multi-Agent Crypto Trading
Four AI agents vote on every crypto trade
Four specialised AI agents — data, sentiment, quant model, verifier — vote together on trades across the top 50 crypto tokens, combining price with news and social signal. Runs 24/7, web UI + API, open-source.
Stack
PythonpandasNumPyscikit-learnLangChainOllamaSQLite
Start your project
30-minute discovery call, fixed-price quote, 4-week roadmap. The next project could be yours.
Book a discovery call
Real reviews
What clients say about us
Quick feedback from people who worked with our team.
5.0
Overall
Based on real reviews
Faster work + consistent output
“Everything got faster and more organized.”
I stopped guessing. Now I follow clear steps and get solid results every time.
Better output + less time
“AI finally feels useful day to day.”
Now I know what to ask and how to get clean outputs for posts, emails, and offers.
Cleaner build + faster execution
“The team helped us improve the system fast.”
They quickly identified what to automate, what to tighten up, and how to structure the system better.
New reviews get added regularly.