Agentic AI, Built for Execution, Engineered for Outcomes
Agentic AI, Built for Execution, Engineered for Outcomes
From A2A coordination and MCP-compliant pipelines to sovereign deployments and self-optimizing models — ALTPAI architects AI that acts, learns, and adapts in real time.
Altpai partner Eco system
Over 90% of enterprise AI pilots fail to move to MVP or production.
— Forbes
The Problems
Inaccurate Output Without Retrieval or Reinforcement
Without RAG or RLHF, off-the-shelf models generate fabricated or imprecise responses and can’t learn from real usage signals.
Insecure, Non-Compliant AI Isn’t Enterprise-Ready
Most AI stacks overlook enterprise-grade controls — from RBAC to zero-trust and MCP alignment — risking compliance from day one.
Generic LLMs. Static Models. Irrelevant Outputs.
Most LLMs ship with no domain tuning, inaccurate responses, low precision, and weak business impact.
PoCs Stall Without Real-World Engineering
AI projects stall at PoC when teams lack retrainable model pipelines and scalable infra built for real-world deployment.
Fragmented Workflows and Manual Handoffs
Disconnected tools, siloed systems, and manual handoffs block automation, stall velocity, and waste engineering cycles.
Generic LLMs. Static Models. Irrelevant Outputs.
Most LLMs ship with no domain tuning, inaccurate responses, low precision, and weak business impact.
Insecure, Non-Compliant AI Isn’t Enterprise-Ready
Most AI stacks overlook enterprise-grade controls — from RBAC to zero-trust and MCP alignment — risking compliance from day one.
Why AI Initiatives
Stall at Scale
PoCs Stall Without Real-World Engineering
AI projects stall at PoC when teams lack retrainable model pipelines and scalable infra built for real-world deployment.
Fragmented Workflows and Manual Handoffs
Disconnected tools, siloed systems, and manual handoffs block automation, stall velocity, and waste engineering cycles.
Inaccurate Output Without Retrieval or Reinforcement
Without RAG or RLHF, off-the-shelf models generate fabricated or imprecise responses and can’t learn from real usage signals.
Why AI Initiatives Stall at Scale
Most LLMs ship with no domain tuning, inaccurate responses, low precision, and weak business impact.
AI projects stall at PoC when teams lack retrainable model pipelines and scalable infra built for real-world deployment.
Disconnected tools, siloed systems, and manual handoffs block automation, stall velocity, and waste engineering cycles.
Most AI stacks overlook enterprise-grade controls — from RBAC to zero-trust and MCP alignment — risking compliance from day one.
Without RAG or RLHF, off-the-shelf models generate fabricated or imprecise responses and can’t learn from real usage signals.
The solution
How We Solve What Holds AI Back
Our Agentic AI systems and productized delivery frameworks eliminate execution bottlenecks and operationalize real-world intelligence at scale.
For Your Existing Stack
We fine-tune models on your domain data and workflows — improving context alignment, reducing factual drift, and driving measurable business outcomes.
- Train on regulated, proprietary, and task-specific datasets
- Inject tool use, embeddings, and retrieval for reasoning
- Optimize for accuracy, latency, and business KPIs
For Cloud & On-Prem
We fine-tune models on your domain data and workflows — improving context alignment, reducing factual drift, and driving measurable business outcomes.
- Train on regulated, proprietary, and task-specific datasets
- Inject tool use, embeddings, and retrieval for reasoning
- Optimize for accuracy, latency, and business KPIs
That Learn, Adapt, and Scale
We fine-tune models on your domain data and workflows — improving context alignment, reducing factual drift, and driving measurable business outcomes.
- Train on regulated, proprietary, and task-specific datasets
- Inject tool use, embeddings, and retrieval for reasoning
- Optimize for accuracy, latency, and business KPIs
That Ships with Compliance Built-In
We fine-tune models on your domain data and workflows — improving context alignment, reducing factual drift, and driving measurable business outcomes.
- Train on regulated, proprietary, and task-specific datasets
- Inject tool use, embeddings, and retrieval for reasoning
- Optimize for accuracy, latency, and business KPIs
Custom Models & LLM
We fine-tune models on your domain data and workflows — improving context alignment, reducing factual drift, and driving measurable business outcomes.
- Train on regulated, proprietary, and task-specific datasets
- Inject tool use, embeddings, and retrieval for reasoning
- Optimize for accuracy, latency, and business KPIs
We Engineer What Others Only Recommend
Not a dev shop. Not a slideware firm. Altpai is where strategic design meets production-grade delivery with agentic AI systems that retrain and scale.
We build agents that think, plan, and act — enabling contextual reasoning far beyond prompt-based models.
- Persistent memory and scratchpad context
- Planning loops (ReAct) with dynamic tool use
- Task graphs for multi-step execution
Altpai agents self-orchestrate tasks using A2A protocols, action policies, and event-driven workflows — no human handoffs needed.
- Agent-to-agent routing and state interpreters
- Action policies with task awareness
- Event-driven orchestration via LangGraph or Temporal.
Your systems learn in the wild — with RAG pipelines, feedback ingestion, and auto-retraining built directly into production.
- Real-time retrieval-augmented generation (RAG)
- Feedback loops + RLHF hooks
- Auto-labeling and retrain triggers
We deploy compliant AI stacks designed for scale across cloud, hybrid, or sovereign environments, with zero-trust by default.
- RBAC, encryption, and tokenized access
- Multi-cloud and sovereign-ready deployments
- MCP-compliant infrastructure and observability
Our AI squads ship productized outcomes — from PoC to retrainable MVPs to scaled orchestration — in agile sprints.
- Integrated teams: PM + MLOps + LLM engineers
- Sprint-based delivery and versioning
- Built-in model release + monitoring pipelines
From Token Generators to Intelligent Agents
We build agents that think, plan, and act — enabling contextual reasoning far beyond prompt-based models.
- Persistent memory and scratchpad context
- Planning loops (ReAct) with dynamic tool use
- Task graphs for multi-step execution
From Manual Prompts to Autonomous Coordination
Altpai agents self-orchestrate tasks using A2A protocols, action policies, and event-driven workflows — no human handoffs needed.
- Agent-to-agent routing and state interpreters
- Action policies with task awareness
- Event-driven orchestration via LangGraph or Temporal
From Static Models to Embedded Retraining
Your systems learn in the wild — with RAG pipelines, feedback ingestion, and auto-retraining built directly into production.
- Real-time retrieval-augmented generation (RAG)
- Feedback loops + RLHF hooks
- Auto-labeling and retrain triggers
From Generic Deployments to Enterprise-Ready Infra
We deploy compliant AI stacks designed for scale across cloud, hybrid, or sovereign environments, with zero-trust by default.
- RBAC, encryption, and tokenized access
- Multi-cloud and sovereign-ready deployments
- MCP-compliant infrastructure and observability
From Advice Decks to Delivered MVPs
Our AI squads ship productized outcomes — from PoC to retrainable MVPs to scaled orchestration — in agile sprints.
- Integrated teams: PM + MLOps + LLM engineers
- Sprint-based delivery and versioning
- Built-in model release + monitoring pipelines
Industries We Serve
We deliver tailored, transformative AI solutions that accelerate innovation and optimize outcomes across key industries worldwide.
Government
Government
We design compliant, explainable AI agents for citizen services, secure document processing, and intelligent routing across sovereign or air-gapped infrastructures.
Explore Government AI Solutions
Startups
Startups
From 0→1, Altpai builds fast, modular MVPs with agentic backends, retrainable loops, and cloud-agnostic deployments — ready to scale.
Start Building Your AI MVP
Finance
Finance
Altpai builds agentic systems for real-time fraud detection, dynamic risk modeling, and personalized recommendations, while meeting strict audit and compliance standards.
Explore Finance AI Solutions
Energy Utilities
Energy Utilities
Altpai powers anomaly detection, predictive maintenance, and real-time agent dispatch — optimizing field operations while ensuring safety and uptime.
Modernize Utility AI Operations
Health
Health
We engineer secure, explainable agents for clinical decision support, triage automation, and adaptive patient journeys — built for HIPAA and safety-critical use.
Build Healthcare AI with Altpai
Education
Education
We deploy agentic tutors that adapt to learning styles, auto-grade assignments, and integrate with LMS and curriculum workflows securely.
Deploy AI in EducationWhat 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.”
Insights
We deliver tailored, transformative AI solutions that accelerate innovation and optimize outcomes across key industries worldwide.
What Is Agentic AI (And How It Works)
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Deploying MCP-Compliant AI in Sovereign Clouds
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Unblocking the PoC-to-MVP Bottleneck
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You Bring the Vision. We Engineer the AI.
Your business goals, our AI systems — built to scale with security, speed, and real-world performance.