We're a custom software company that builds production systems for regulated industries. Platforms serving 300,000+ policyholders. Document ecosystems processing 40,000+ documents a week. AI agents that cut 20-hour workflows to 10-15 minutes. Two decades of shipping software that works.
We also build AI agents embedded directly in your product, not alongside it. Copilots, document processing agents, knowledge agents, conversational agents, and voice agents. Every agent runs on HyperCore, our proprietary agentic framework with 5,000+ eval assertions, built-in governance, and HyperCare post-launch support. Production-ready and measured.

We treat AI as a general capability valuable only when it improves a workflow inside your product. HyperSense provides AI software development, AI consulting services, and AI integration services alongside custom web and mobile engineering.
We’re ISO/IEC 27001 & 9001 certified, model-agnostic, and outcome-focused, so you get application-level AI that’s secure, governed, and measured.











We start from your business process and KPI, then deploy AI agents that remove friction and deliver measurable results. Every agent ships on HyperCore with eval-driven quality gates and HyperCare post-launch support.
1.
We align on business objectives and KPIs, not just features. Identify quick wins for AI agent deployment. Run an AI readiness check: data sources, systems, constraints, and success metrics.
2.
Define where AI shows up in your product and how it helps. Choose the right approach: knowledge agents, document processing, conversational AI, agentic workflows. Model-agnostic from the start. Security and governance planning included.
3.
Design assistive UX with clear states, explanations, citations, and approval flows. Build the agent inside your app. Integrate with your systems and data. Keep vendor choices flexible.
4.
Functional tests plus AI-specific evaluations: quality, faithfulness, safety, and latency. 5,000+ eval assertions validate agent behavior before production. Human-in-the-loop validation where accuracy and compliance matter. We validate that the feature moves the KPI we agreed on.
5.
Launch with observability and cost guardrails. Usage dashboards, budgets, alerting. Training and runbooks so your team adopts the feature. HyperCare post-launch support for both the application and the AI components.
6.
Measure impact against your baseline. A/B tests and user feedback. Tune prompts, improve data coverage, optimize costs. Model-agnostic stance means you can switch models as your needs evolve.
Need speed? Try the AI Feature Sprint (≈4 weeks)
Pick one high-leverage use case; we design, build, harden, and ship a production feature with evaluation, governance, and KPI tracking so you see value fast.
Proptech
98% time reduction. 20+ hours to 10-15 minutes. Claude 4.5 Sonnet on AWS Bedrock. Live at agent.reperks.de. Document processing, legal compliance automation, triple-validated calculations. 6-week MVP, 5-person team.
Insurance
300,000+ policyholders. 100,000+ downloads. 1,400+ clinics. 16% YoY premium growth. Cross-platform insurance platform across iOS, Android, and web. 2+ year engagement, 8-person team.

Fintech
50,000+ users in 3 months. EUR 300,000+ monthly transaction volume. 4.8 App Store / 5.0 Google Play ratings. Flutter cross-platform BNPL app with serverless AWS infrastructure. 10+ year partnership.
Our technological skills span modern web, mobile, and cloud. Whether you need custom software development, AI agent development, or mobile apps, we build production systems governed for security, quality, and cost.
Languages
HTML5, CSS3, JavaScript/TypeScript
Frameworks/Libraries
React, Angular, Vue.js
AI in the UI
Assistive UX (copilot panels, explainability/citations, approvals), accessibility, analytics for AI feature adoption
Languages
Node.js, Python, Java, .NET, PHP
Frameworks
Express/Fastify, FastAPI, Spring Boot, ASP.NET Core, Laravel
Data & events
REST/GraphQL, Webhooks, event-driven patterns for agent actions and automations
Native
Swift (iOS), Kotlin (Android)
Cross-platforms
Flutter, React Native
AI on mobile
In-app copilots, smart capture (IDP), voice, on-device friendly patterns (caching/offline)
Primary
AWS (Partner), plus Azure, Google Cloud Platform
Common services
Serverless (Lambda/Functions), containers (ECS/Fargate/Kubernetes), object stores, managed DBs, CDN, secrets/keys
Model access
Amazon Bedrock and Anthropic Claude (primary stack). Model-agnostic routing and prompt caching
RAG/Knowledge
Vector search (pgvector, OpenSearch, Pinecone, Weaviate). Classification-first document processing with human-in-the-loop
IDP (Document AI)
Classification → extraction → validation → posting, with human-in-the-loop
Agentic workflows
Tool and function calling, approval lanes, action logs
Interop
(Optional) MCP-ready integrations to expose safe tools/data to agents
Pipelines/lakes
AWS Glue/Athena, EMR, Step Functions, Airflow, dbt; S3/Parquet; Lakehouse (Delta/Iceberg)
Streams
Amazon Kinesis, Kafka
Warehouses
Redshift, BigQuery, Snowflake
BI/observability
Dashboards for KPI impact, usage, and cost of AI features
MLOps consulting
Monitoring, regression tests, drift checks
Eval & safety
Quality/ faithfulness/ safety/ latency scorecards; red-teaming; guardrails
Cost control
Token budgets, prompt caching, tiered model routing, usage alerts
Telemetry
CloudWatch, OpenTelemetry, Datadog feature-level metrics
Tools
Docker, Kubernetes, Terraform, GitHub Actions, GitLab CI/CD, Jenkins
Practices
Blue/green and canary deploys, feature flags, automated rollbacks for AI-powered features
Standards
ISO 9001:2015, ISO/IEC 27001:2018; GDPR/CCPA alignment
Access
SSO/SAML, OAuth 2.0/OIDC, RBAC, agent identities & least-privilege policies
Data
Encryption in transit/at rest, customer-managed keys, PII/PHI handling, audit logs, data residency options
Controls
Model/data-usage policies (your data is never used to train third-party models without consent)
Protocols
MQTT, CoAP, HTTP
Platforms
AWS IoT Core, Azure IoT Hub
Use in AI
Device telemetry → anomaly detection, predictive maintenance, automated workflows
Tech
WebRTC, VoIP/SIP, streaming (HLS, MPEG-DASH)
Use in AI
Real-time voice assistants, call summarization, coaching, and automated follow-ups
Tools
Figma, Adobe XD, Sketch
Practices
Wireframing, assistive UX patterns (explanations, citations, confidence states), user testing for AI features
Your data is never used to train third-party models without consent. Model-agnostic, secure, and measurable — we integrate AI directly into your product and prove the impact.

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Ready to build something that works?
Walk away from the first call with a scoped plan, a timeline, and a cost estimate. Whether you need a production AI agent, an enterprise platform, or a team to augment yours, we’ll map the path from idea to production.
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