Agentic AI Augmentation: Transform Legacy Systems into Autonomous Intelligence
We don’t just integrate agents — we engineer adaptive, self-learning AI that wraps around your existing systems to reason, collaborate, and evolve. Built for legacy environments, our agentic layer enhances capabilities while upholding enterprise-grade compliance, governance, and control.
Most AI doesn’t fail from lack of intelligence — it fails from missing orchestration, oversight, and system integration.
Key Offerings
Intelligent Legacy Integration
We don’t ask you to replace what works. Instead, we wrap your legacy systems with agentic intelligence to automate, orchestrate, and enhance without disruption.
- Agent overlays for legacy systems: Add intelligence to CRMs, ERPs, and internal apps without replacing them.
- Retrieval from siloed data: Use embeddings and RAG to unlock answers from outdated or unstructured databases.
- API-wrapped orchestration: Turn static systems into dynamic workflows using intelligent API wrappers.
- No-rebuild automation: Modernize workflows without disrupting existing infrastructure.
Intelligent Legacy Integration
We don’t ask you to replace what works. Instead, we wrap your legacy systems with agentic intelligence to automate, orchestrate, and enhance without disruption.
- Agent overlays for legacy systems: Add intelligence to CRMs, ERPs, and internal apps without replacing them.
- Retrieval from siloed data: Use embeddings and RAG to unlock answers from outdated or unstructured databases.
- API-wrapped orchestration: Turn static systems into dynamic workflows using intelligent API wrappers.
- No-rebuild automation: Modernize workflows without disrupting existing infrastructure.
Cross-System Agent Collaboration
We build AI agents that communicate across departments and platforms — enabling intelligent orchestration of data, tasks, and decisions without human handoffs.
- Cross-platform task delegation: Automate workflows that span CRM, ERP, support, finance, and more.
- Process-aware agents: Coordinate between departments (e.g., sales + legal + finance) using shared task memory.
- Smart routing engines: Agents that triage requests, assign actions, and sync results across teams.
- Silo-to-system unification: Eliminate disconnected workflows with agents that integrate APIs, docs, and tools.
Cross-System Agent Collaboration
We build AI agents that communicate across departments and platforms — enabling intelligent orchestration of data, tasks, and decisions without human handoffs.
- Cross-platform task delegation: Automate workflows that span CRM, ERP, support, finance, and more.
- Process-aware agents: Coordinate between departments (e.g., sales + legal + finance) using shared task memory.
- Smart routing engines: Agents that triage requests, assign actions, and sync results across teams.
- Silo-to-system unification: Eliminate disconnected workflows with agents that integrate APIs, docs, and tools.
Human-in-the-Loop & Reinforcement Learning
We embed human feedback loops into your AI systems so agents can improve continuously, learning from real usage, not just static data.
- Validation & escalation loops: Let humans intervene when agents need clarification or approval.
- RLHF integration: Use human feedback to shape model behavior and alignment.
- Preference learning systems: Train agents to adapt based on evolving team or user preferences.
- Behavior tuning from telemetry: Continuously improve agent actions using real-world usage data.
Human-in-the-Loop & Reinforcement Learning
We embed human feedback loops into your AI systems so agents can improve continuously, learning from real usage, not just static data.
- Validation & escalation loops: Let humans intervene when agents need clarification or approval.
- RLHF integration: Use human feedback to shape model behavior and alignment.
- Preference learning systems: Train agents to adapt based on evolving team or user preferences.
- Behavior tuning from telemetry: Continuously improve agent actions using real-world usage data.
Microsoft Cloud Principles (MCP) Compliance
We architect AI deployments to align with MCP, ensuring your systems meet the highest bar for data sovereignty, compliance, and operational rigor.
- MCP-aligned deployment patterns: Architected for identity, access, governance, and audit.
- Zero-trust enforcement: Tokenized access and RBAC built into every layer.
- Sovereign & hybrid cloud readiness: Designed for compliance across multi-cloud, sovereign, and on-prem environments.
- Microsoft-native integration: Built to inherit and align with Microsoft’s secure-by-design approach.
Microsoft Cloud Principles (MCP) Compliance
We architect AI deployments to align with MCP, ensuring your systems meet the highest bar for data sovereignty, compliance, and operational rigor.
- MCP-aligned deployment patterns: Architected for identity, access, governance, and audit.
- Zero-trust enforcement: Tokenized access and RBAC built into every layer.
- Sovereign & hybrid cloud readiness: Designed for compliance across multi-cloud, sovereign, and on-prem environments.
- Microsoft-native integration: Built to inherit and align with Microsoft’s secure-by-design approach.
Self-Learning LLMs in Production
Your models shouldn’t go stale. We build learning loops into every deployment so systems retrain, refine, and adapt automatically as the world changes.
- Live feedback ingestion: Capture user behavior, corrections, and telemetry in real time.
- Auto-labeling pipelines: Reduce manual work with automated data tagging and classification.
- Retrain triggers & workflows: Refresh models continuously without downtime.
- Adaptive RAG + fine-tuning: Evolve responses based on usage, seasonality, or new data.
Self-Learning LLMs in Production
Your models shouldn’t go stale. We build learning loops into every deployment so systems retrain, refine, and adapt automatically as the world changes.
- Live feedback ingestion: Capture user behavior, corrections, and telemetry in real time.
- Auto-labeling pipelines: Reduce manual work with automated data tagging and classification.
- Retrain triggers & workflows: Refresh models continuously without downtime.
- Adaptive RAG + fine-tuning: Evolve responses based on usage, seasonality, or new data.
What Clients Say About Altpai
“Altpai helped us layer agentic workflows over legacy systems without rewriting a single core module. We got automation, orchestration, and observability without disruption. Their team understood both the tech and the enterprise risk. More than a deployment, it was a precision retrofit built to scale with our operational architecture.”
“Altpai engineered our AI infrastructure to be fully cloud-agnostic, with telemetry, RBAC, and security protocols embedded from day zero. Their approach was foundational. We now have an AI-native stack that meets compliance, scales predictably, and integrates seamlessly across Azure, AWS, and our sovereign deployment zones.”
“Our initial LLM plateaued at 40% accuracy. Altpai overhauled it with RAG, embeddings, and a feedback loop for retraining. Within weeks, the system was self-improving in production, accurate, relevant, and context-aware. Now, it’s a living system embedded in our decision workflows.”
“Altpai deployed a fraud detection engine that detects and evolves. With agentic logic and daily retraining, our false positives dropped dramatically. What impressed me most was the zero-lag adaptation. This isn’t just AI but operational intelligence that learns on the job.”
“Our PoC was production-ready in just four weeks. By week eight, Altpai had built a retrainable MVP, fully instrumented and aligned to our GTM strategy. No bloated dev cycles. No handovers. Just velocity, quality, and the infrastructure to scale. They didn’t consult; they executed.”