Agentic AI That Acts
Before the Problem Occurs
We design and build agentic AI systems that continuously monitor the signals your teams don't have time to watch — and surface decisions before disruptions become crises.
Designed for VPs of Supply Chain, Operations, and CIO and enterprise technology leaders in complex, multi-node networks.
Available for organizations with $500M+ in annual revenue.
In 30 Seconds
Business Outcomes
15–25% reduction in disruption costs · 60–90 day earlier risk detection · 70–80% less manual monitoring burden
Time to PoC
Working agent running against your real data in 4–6 weeks · Full production in 10–12 weeks
Risk Posture
Human-in-the-loop by design · No autonomous writes to ERP · Decision rationale and trace logs on every agent action
What Is Agentic AI?
Traditional AI tools answer questions when asked. Agentic AI systems act — continuously, autonomously, and with a human in the loop for final authority.
Example: A port strike is reported in Rotterdam. Within 15 minutes the agent has identified the 23 SKUs on affected vessels, flagged the 4 warehouses at stockout risk, and proposed two re-routing options with cost comparisons — ready for your logistics coordinator to approve with one click.
Continuous Monitoring
The agent watches structured and unstructured data streams around the clock — not just when a human checks a dashboard.
Contextual Reasoning
An LLM makes sense of unstructured signals — news, weather, social data — and connects them to your internal inventory, orders, and logistics state.
Human-Approved Action
Every proposed action goes through a human approval layer. The agent does the heavy analytical work; your team reviews the cost-benefit analysis and makes the final call.
Our Methodology: ARIA
Agentic Reasoning for Intelligent Action
Signal Mapping
Outcome: complete inventory of risk signals across your systems in 2 weeks
We map every data source that affects your operations — internal systems, external feeds, and the gap between them. Most enterprises are surprised by how many signals exist that their systems never see.
Reasoning Architecture
Outcome: agent reasoning tuned to your domain vocabulary and decision types — not a generic chatbot
We design the AI reasoning chain and context retrieval strategy specific to your risk tolerance and data model. Off-the-shelf LLMs produce generic outputs; our architecture produces decisions your team can act on.
Proof of Concept — 4 to 6 Weeks
Outcome: working agent on your real data, integrated with your legacy ERP/WMS — no disruption to existing systems
We build against a scoped subset of your data. A production-relevant prototype running on real enterprise data — ingesting live signals, generating proposed actions, and proving the architecture integrates without disruption to existing systems.
Production & Iteration
Outcome: full production deployment with embedded support through the first 90 days
We scale the PoC to full production and establish a feedback loop so the agent's reasoning improves with each decision cycle. We stay embedded as a partner — not a vendor who disappears after launch.
Reference Architectures
Proven blueprints, adapted to your stack
Metrics below are representative outcome targets modeled from reference implementations. Actual results depend on data quality, integration scope, and operating environment.
Why Sahaya for Enterprise AI
Architecture Before Code
We produce a full PRD and system design before a line of code is written. You see exactly what you're buying and why each component exists — no black boxes, no surprises in month three.
Domain-Specific Reasoning
Generic AI wrappers produce generic outputs. We tune the reasoning chain to your industry vocabulary, your risk thresholds, and your data model — so the system reasons against your business constraints, not a generalized approximation of them.
Audit Trail by Default
Every agent action is logged with its decision rationale, input signals, and trace record. Compliance teams, governance reviewers, and postmortem investigations all have what they need — without exposing proprietary model internals.
Embedded Partnership
We don't hand off and disappear. Sahaya stays embedded through the first 90 days of production, iterating the agent's reasoning as your team's feedback reveals edge cases the design didn't anticipate.
Start the Conversation
Request an Executive Briefing
Share your details and we'll reach out within one business day to schedule.
Ready to Talk?
We offer a no-obligation executive briefing: 60 minutes with your leadership team. We map one critical operational flow, identify 3–5 candidate agentic use cases, and outline a 4–6 week PoC plan — with a working architecture sketch in hand by the end.
This is a fit if your organization has:
- A complex, multi-node supply chain, portfolio, or compliance program
- Data fragmented across ERP, WMS, TMS, or GRC systems that don't talk to each other
- High cost of disruptions, stockouts, defaults, or compliance failures — where early warning is worth millions
Available for organizations with $500M+ in annual revenue · No obligation