Build AI Agents for Production, Not Pilots
We architect, govern, and scale enterprise-grade AI agents your board approves, finance defends, and customers happily adopt.
Credentials
ISO 27001 Certified
Oracle Partner
SnowflakePartner
AWS Partner
Capability
16+
Years of Experience
250+
Projects Delivered
95%
Customer Retention
200+
AI-first Engineers
WHO THIS IS FOR
For C-Suite Decision Makers Leading Enterprise AI Execution
GrowExx is an AI agent development company delivering custom AI agent development for BFSI, manufacturing, healthcare, retail, and logistics. Our multi-agent systems read, reason, decide, and act inside your existing ERP, CRM, and core platforms — not alongside them — with audit-grade governance built in.
The result is the rarest outcome in enterprise AI agent development: applications a board signs off on, finance defends, and customers happily adopt. Every engagement is scoped backwards from a defended ROI model — cost-per-inference, automation rate, error reduction, and payback window — before a single line of orchestration code is written.
How we put AI into Enterprise
Thee Layers. Pick the Mix that Fits
01
AI & Data Engineering
Data platforms, MLOps, RAG pipelines; the foundation your agent runs on.
02
Custom AI Development
LLM apps, fine-tuning computer vision, predictive models built for your domain
03
GrowExx Products
Recogent, Hirin, Readerr plug straight in.
What we deliver
Our End-to-End AI Agent Development Services
Agent Strategy & Use-Case Mapping
We rank your AI agent backlog by ROI, data readiness, and compliance load, then map exactly where agents belong across your workflows. From design to go-live, with governance; everything is baked in from day one.
Custom AI Agent Development
Our custom AI agent development services engineer single-task and multi-task agents tuned to your domain — finance close, claims triage, demand forecasting, code review, support deflection. Built on RAG, function-calling, and your choice of frontier or open-source LLM.
Multi-Agent Orchestration
Specialist agents that collaborate, hand off, and escalate — supervised by a planner agent and a critic agent.
Enterprise Tool & System Integration
Agents are only as useful as the systems they touch. We integrate with SAP, Oracle, Salesforce, NetSuite, ServiceNow, Snowflake, Databricks, and 200+ SaaS tools via MCP, native APIs, and custom connectors — with full role-based access control.
Evaluation, Observability & Guardrails
Every agent ships with an eval harness, prompt-injection defenses, output validators, cost dashboards, and drift alerts. You see exactly what each agent decided, why, and what it cost — in real time, in a single pane.
Managed AI Agents Operations
Post-launch, we own the operational SLA, including model retraining, prompt tuning, regression testing, vendor migration, and audit readiness, under a fixed-fee MSA. Your team focuses on outcomes, not on chasing hallucinations at midnight.
Industries we serve
AI Agents, configured for how your industry actually runs
Four focus industries. Each with a specific playbook for AI Agents.
The Challenge
A retail bank’s reconciliation team matches 40,000+ daily transactions across core banking, card network files, and Nostro statements. Breaks sit in Excel for 10–14 days. Every flagged item needs an audit-defensible trail before RBI/SEC filing.
How AI Agents Help
We build a Reconciliation Agent on Claude Agent SDK + LangGraph that ingests SWIFT MT940, card scheme files, and core banking extracts; matches at transaction level using a fuzzy-match + LLM-reasoning pipeline; auto-resolves 85%+ of breaks; and routes the rest to an analyst with rationale and source records attached.
Deliverables
A production agent deployed inside your VPC. Eval harness tuned to your reconciliation rules. Versioned audit log (prompt, decision, evidence) per RBI/SEC requirements. Integration with Finacle/T24/Flexcube and your GL via MCP. Analyst review console with one-click approve/escalate.
Quantified Result
10 days → 2
Faster month-end close at a Tier-1 private bank in India.
The Challenge
An auto-components plant runs 14 production lines on PLCs feeding a SAP MES. When a defect spike hits, engineers spend 6–9 hours pulling PLC tags, quality logs, and shift notes to find root cause. Lines run hot or stop.
How AI Agents Help
We build a Root-Cause Analysis Agent that subscribes to MES alarms via MQTT, pulls correlated PLC tag history from OSIsoft PI, reads shift handover notes and 8D reports in SharePoint, and proposes a ranked root-cause hypothesis with evidence. A Maintenance Agent then drafts the work order in SAP PM and assigns by skill and shift.
Deliverables
RCA agent + Maintenance agent on the same orchestrator. PI Historian + SAP MES + SAP PM connectors. Confidence-scored hypotheses with linked telemetry. Auto-drafted work orders requiring supervisor sign-off. Eval suite tested against your last 12 months of incidents. ISO/IATF 16949 audit log.
Quantified Result
9 hrs → 22 min
Mean time-to-root-cause at a global auto-components supplier
The Challenge
A specialty-care network submits 1,200 prior authorizations a week across Aetna, UHC, and BCBS. Each takes 5–10 days, requires payer-specific clinical criteria, and ties up two FTEs. Denials run 18%, mostly for missing evidence — not clinical merit.
How AI Agents Help
We build a Prior-Auth Agent that reads the patient’s Epic chart (problem list, labs, imaging, notes), matches against the payer’s published medical policy, assembles the packet with cited evidence, and submits via the payer portal or 278 transaction. PHI never leaves your VPC. Every output is signed off by a clinician before submission.
Deliverables
Prior-Auth Agent integrated with Epic via FHIR and your clearinghouse via 278/275. Payer-policy retrieval index, refreshed weekly. Clinician review UI with policy citations and chart evidence side-by-side. HIPAA-compliant audit log of every PHI access. Eval suite scored against your last 6 months of approvals/denials.
Quantified Result
18% → 6% denial rate
Prior-auth turnaround at a US specialty-care network
The Challenge
A national fashion retailer runs 240 stores + e-commerce on Shopify Plus, with inventory in Manhattan WMS and orders in NetSuite. Support handles 9,000 tickets/week. Stockouts on top-100 SKUs hit 31% during promos because demand signals lag, and replenishment is weekly.
How AI Agents Help
We build two agents on a shared orchestrator. A Demand & Replenishment Agent forecasts SKU/store daily, watches POS in near real-time, and triggers cross-store transfers and reorders against margin and capacity guardrails. A Customer-Service Agent resolves “where’s my order,” size exchanges, and returns end-to-end across Shopify, Manhattan, NetSuite, and the loyalty CDP — escalating only edge cases.
Deliverables
Two production agents, one orchestrator. Forecast model + reinforcement-learning reorder loop tuned to your SKU history. Shopify/Manhattan/NetSuite/CDP connectors via MCP. Margin and stock-position guardrails enforced in the agent runtime. Auto-resolution + supervisor review queue. A/B harness for prompt and policy changes.
Quantified Result
48 hrs → 4 min
ticket resolution for National fashion retailer
See how we did 10 days → 2 for a similar BFSI client.
Industry-specific reference architecture. 20 minutes. No slides.
How we deliver
Five steps. One discipline. Enterprise AI agents that reach production.
Click any step to see what happens inside it and the tooling we deploy with.
Step 01 · Discovery
Map where AI agents actually belong in your enterprise.
We rank your agent backlog by 12-month payback, data readiness, and compliance load — and write the business case your CFO’s office will sign before a model gets touched.
Output: A defended ROI model and a prioritized backlog of the next enterprise agents
Step 02 · Design
Architect the agent system before a line of enterprise code ships.
We design orchestration, tools, memory, guardrails, and escalation paths — then red-team the system against hallucination, prompt injection, tool misuse, and runaway cost.
Output: An architecture review signed off by Security, Legal, and IT, plus a written eval plan tied to your acceptance thresholds.
Step 03 · Build
Engineer enterprise agents, evals, and human-in-the-loop in parallel.
Every commit runs through automated evals. Observability and the reviewer UX are wired in from day one — not bolted on after the demo.
Output: A staging-grade enterprise agent passing your acceptance benchmarks, with full eval coverage and observability live.
Step 04 · Pilot
Ship a controlled enterprise pilot — and harden before you scale.
We run against a pre-set acceptance threshold, then harden security, observability, and cost-per-task economics before broad rollout across business units.
Output: A production agent live inside your enterprise environment, plus a quarterly ROI review cadence with the business owner.
Step 05 · Operate
Own the agent’s compounding value across the enterprise, not just its launch.
Under a fixed-fee MSA, we own retraining, prompt versioning, drift detection, model-vendor migrations, and audit readiness — so the agent improves quarter over quarter instead of decaying after go-live.
Output: A quarterly board-grade scorecard — usage, freshness, cost-per-query, and payback.
Why GrowExx
Why Choose GrowExx for AI Agent Development
01
ROI Defended Before Code Is Written
We refuse projects without a defended payback model. If we cannot prove 12-month ROI on paper, we will not put it on a roadmap. That discipline is why our agents survive budget reviews — and why our clients renew.
02
Vendor-Neutral by Design
We are not paid to push GPT, Claude, Llama, or Gemini. Every engagement starts with a model-routing decision based on accuracy, cost, latency, and data residency — not vendor incentive. You walk away with a stack you can swap, not a stack you are stuck with.
03
Built-in Governance, not Bolted On
Audit trails, prompt versioning, output validation, PII redaction, and human-in-the-loop escalation are part of the foundation — not features added when legal pushes back. Pass internal audit and external regulator scrutiny on day one.
04
95% Client Retention
95% clients extend the engagement. Not because they have to, because we ship outcomes, not invoices.
05
Fixed Outcome Pricing Available
Tired of T&M scope creep? We offer fixed-outcome contracts on most AI agent engagements. You pay for results, we absorb estimation risk.
06
AI-Driven Development
Our 8-agent autonomous dev workflow cuts delivery cycles by up to 40%. Same quality, shipped cleaner, on shorter timelines.
Explore how AI Agent Development Services can help
Selected work
Real-World AI Agents Case Studies & Success Stories
Explore our latest case studies to see exactly how we deliver ROI for brands just like yours.
Artificial Intelligence
Revolutionizing HR Policy Management: A Generative AI Solution for a Logistics Company
In the modern corporate setting, effective HR policy management is one of the key elements in ensuring organizational governance and contentment among employees while creating an environment that allows business to run smoothly. Client Overview…
Artificial Intelligence
Business Intelligence Solution built on Big Data for Internet Telephony Enterprise
Growexx provided a dedicated team that worked as an extended part for an MNC offering business intelligence solutions for big data analytics.
Artificial Intelligence
Funding Platform To Help Budding Musicians
GrowExx helped in launching a funding platform to help budding musicians with no strings attached.
Artificial Intelligence
Creating a Product Roadmap for AI-powered Career Counselling System
GrowExx team held a product discovery session to chalk out a product roadmap to create an AI-powered career counselling system.
Artificial Intelligence
Digitizing Culinary Heritage: Transforming Handwritten Reviews with NLP
In the heart of Paris, a leading restaurant that has been operating for decades faced a challenge. The reviews by customers were hand-written about their experience at the eatery. Thus, there was a need…
Artificial Intelligence
From Bidding to Winning: The Tender Automation Success Story
In this fast-paced environment of tender acquisition, precision is the keynote to success. This study highlights the transformative partnership between a leading IT Hardware & Networking company and GrowExx, and how innovative solutions completely transformed…
What our clients say
The CFOs and CIOs we've worked with.
"
GrowExx is the only partner who refused to start coding until we agreed on the ROI math. That discipline is exactly why our reconciliation agent shipped on time, on budget.
CFO
Global Finance Group
AI Agents
BFSI
"
We had three AI vendors. Two showed us demos. GrowExx showed us the eval harness, the cost-per-task dashboard, and the rollback plan. That's why they got the contract — and the renewal.
VP Operations
Apex Enterprise
Enterprise AI
Logistics
"
Their team treats every agent like a regulated piece of software, not a science project. That's the difference between a pilot you brag about and an agent your auditor signs off on.
Chief Risk Officer
Vanguard Manufacturing
AI Agents
Manufacturing
Talk to the team behind these outcomes.
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Featured Product
Recogent — an AI agent built for the reconciliation problem this page describes.
A pre-built AI agent, deployed in weeks. Handles bank, GL, AR, AP, intercompany, and fixed-asset reconciliation with AI that surfaces only the exceptions you need to touch.
Recogent· Live metrics
99%
Less manual effort
99%
Match accuracy
<4 wk
to go live
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