AI that plans,
reasons, and
executes.
Agentic AI systems with defined autonomy boundaries, audit trails, and human oversight mechanisms, built for operational environments where accountability is non-negotiable.
Ask AI about this service
Agentic AI moves beyond question-answering. It plans multi-step workflows, reasons over context, calls tools and APIs, and executes actions, with guardrails that define what it can and cannot do autonomously. For operational organisations, this means AI that monitors asset health and triggers maintenance workflows, processes procurement documents through approval logic, or synthesises intelligence from multiple data sources into decision-ready briefings, all within a governance framework your institutional stakeholders can audit.
What we build.
Orchestration
LLM orchestration with tool use and function calling, governed by a structured execution plan and permission boundaries.
Multi-Agent Workflows
Supervisor, worker, and synthesis agents coordinated to match your real workflow, with explicit handoffs and shared memory.
Guardrails & Governance
Autonomy with accountability: scoped guardrails, human-in-the-loop checkpoints, full trace logging, and rollback.
Operational Integrations
Safe, audited agent access to ERP, CMMS, document stores, and internal APIs, with reversible, attributable write-backs.
Where agentic AI operates.
Agentic systems deliver value where the workflow is too variable for a fixed automation script, but too consequential to leave to a general-purpose LLM with no guardrails.
Maintenance workflow automation
Agents monitor asset health telemetry, identify anomalies, generate maintenance recommendations, and route work orders through the approval chain, without replacing the engineer’s judgement.
Procurement document processing
Inbound tender documents, GFR compliance checks, and vendor correspondence processed, classified, and routed by agents that surface decision-ready summaries for procurement officers.
Intelligence synthesis and briefing
Agents pulling from multiple operational data sources, sensor feeds, reports, databases, and news, to synthesise situation-aware briefings for operations leadership on a scheduled or triggered basis.
Compliance monitoring agents
Continuous monitoring agents that flag deviations from regulatory or contractual obligations, generate audit-ready evidence packages, and escalate to the relevant function.
Field data collection and processing
Agents connected to field inspection apps that process unstructured observations, classify defects against a standard taxonomy, and push structured records into the asset management system.
Customer and supplier communication
Agents handling first-response communications, answering procurement queries, acknowledging inspection reports, and triaging inbound requests, within a defined policy boundary.
A working agent on one real task in 10 days.
From the day you engage us, not from a kickoff weeks later. Every milestone is a result you can see.
- Day 2
Workflow mapped, autonomy limits and approval points agreed
- Day 10
First agent running on a live task with full action logging
- Day 30
Production release with evaluation suite and escalation paths
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Fixed scope
Scope, price, and milestones are agreed before work starts.
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No surprises
Weekly demos and plain-language status. Changes are priced before they are built.
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Compliance from day one
Autonomy boundaries, approval gates, and tamper-evident audit trails are part of the first build, not a later hardening phase.
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You own the IP
Code, models, and documentation transfer to you on successful handover.
Know the price, the date,
and the exit before we start.
Fixed-scope project. A defined deliverable at a fixed price and date. Payment is released as each milestone is accepted. The same terms are written into every statement of work for agentic ai systems, so there is nothing to discover later.
- Quote Within 5 working days Price per milestone, dates, and named architect
- Priced One price per milestone Third-party costs listed separately, at cost. Invoiced in USD for international clients
- Paid On accepted working software Not on calendar dates or hours logged
- Changes Written and priced first Cost and date impact before work starts
You fund accepted work, never a promise.
Drag to move through the engagement. Money is released only as each gate is accepted, so what you have paid never runs ahead of what you can use.
- Milestone 1Day 2
Workflow mapped, autonomy limits and approval points agreed
Accepted whenWorking software demonstrated against the written acceptance criteria.
Releases 20% - Milestone 2Day 10
First agent running on a live task with full action logging
Accepted whenWorking software demonstrated against the written acceptance criteria.
Releases 30% - Milestone 3Day 30
Production release with evaluation suite and escalation paths
Accepted whenWorking software demonstrated against the written acceptance criteria.
Releases 30% - HandoverAt final acceptance
Code, architecture documents, deployment scripts, and credentials transferred to you.
Accepted whenFinal acceptance signed. Defects then fixed under warranty at no charge.
Releases 20%
Illustrative split. The exact percentages and dates are fixed in your statement of work.
When something goes wrong, who pays?
Every project meets surprises. What matters is who carries them. Pick one and compare how three commercial models respond.
The hours keep running while the team investigates. You pay for the surprise.
A change request is raised, usually priced at a premium and argued over.
We verified it before quoting, and the risk register held an allowance. Any overrun beyond it is ours.
It is absorbed into the hours. The date slips quietly and you learn at the invoice.
A change fee arrives, often as a lump sum with little explanation.
You get a written amendment with cost and date impact. Nothing starts until you approve it.
You pay for the difference. The estimate was only ever a guess.
The vendor reopens scope to recover margin, or cuts corners to hold it.
The price stays fixed. The overrun is ours to carry, and you see the budget position at every demo.
It is billed on the calendar anyway. The status report says "on track".
The invoice follows the date in the contract, whether or not the work is done.
Payment for that milestone is held until it passes the written criteria. You do not fund a miss.
One price, built in the open.
The proposal itemises every feature or milestone, names its assumptions, and keeps a risk register with allowances. Allowances you never use are not billed.
- Data readiness and volume
- Accuracy or quality bar to be met
- Deployment: on-prem, private VPC, or air-gapped
- Number of workflows or use cases
A representative data sample is available in week one.
If falseWe re-baseline the accuracy target and price together, in writing.
The quality bar is a number agreed up front, measured on your data.
If falseMoving the bar is a costed change request, not a quiet scope drift.
Hardware for private deployment is provisioned by Day 7.
If falseDates move by the delay. The price does not change.
- Cloud hosting
- Third-party licences
- Model and API usage
Invoiced in USD for international clients, with the currency fixed in the SOW. You own it. Code, models, documents, and credentials transfer on payment.
Built on a production-grade stack.
We pick tools proven in production and maintainable over long lifecycles - not whatever is trending. These are a few we reach for here; explore the full stack behind our engineering.
Explore our technology stack →
Articles on Agentic AI Systems
All articles→What buyers ask before they commit.
Straight answers on timelines, price, risk, and ownership, the same terms that appear in every proposal.
01What is Agentic AI Systems?
Agentic AI systems that plan, reason, and execute multi-step workflows with audit trails and human oversight. Built for high-accountability enterprises and PSUs.
02How quickly does Agentic AI Systems deliver a first result?
A working agent on one real task in 10 days. Typical milestones are Day 2: workflow mapped, autonomy limits and approval points agreed; Day 10: first agent running on a live task with full action logging; Day 30: production release with evaluation suite and escalation paths. Exact dates are written into the statement of work before you commit.
03How is Agentic AI Systems priced?
Fixed-scope project: one price per milestone, with a first-release date, itemised in a statement of work within five working days of scoping. Payment is released as each milestone is accepted against written criteria. Cloud hosting, licences, and model usage are passed through at cost. International clients are invoiced in USD. The main price drivers are data readiness and volume, accuracy or quality bar to be met, deployment: on-prem, private VPC, or air-gapped, number of workflows or use cases.
04What happens if the scope changes or the work overruns?
The price stays fixed. A change to scope is quoted in writing, with its cost and date impact, and starts only after you approve it. If our own estimate was wrong, the overrun is ours, not yours. You see the budget position against milestones at every demo.
05Who owns the code, models, and documentation?
You do. Code, models, and documentation transfer to you on successful handover. Code, architecture documents, deployment scripts, and credentials transfer on payment, with no licence back.
06How are security and compliance handled?
Autonomy boundaries, approval gates, and tamper-evident audit trails are part of the first build, not a later hardening phase.
07Do you work with clients outside India?
Yes. We are based in Noida and work with clients around the world, delivering remotely. Calls and demos are scheduled in your time zone, proposals and contracts are in English, international clients are invoiced in USD, and every engagement follows the same fixed-scope terms regardless of where you are.
08When would you decline to fix a price?
Open-ended research has no end date, so we time-box it. We commit a fixed fee to reach a measured baseline, and decide the next step with you from the evidence.
Agentic AI that works in the real world.
If you have a workflow that is too variable for standard automation and too consequential for an unguarded LLM, we can scope an agentic architecture around it. Start with a technical conversation, we will tell you whether the use case fits and what the accountability architecture needs to look like.