An innovative agentic workflow product from AlgoProfessor AI R&D Solutions, Hyderabad Main website: www.algoprofessor.com ↗All products: products.algoprofessor.com ↗
AlgoProfessor AI R&D Solutions · Hyderabad New · 2026

AlgoProfessor Innovative Agentic Workflow Product

AlgoCrew OS·Agentic AI Workflow Platform for Software Companies

A software company, staffed by twelve agents and led by you.

AlgoCrew OS gives your firm a full AI operating team: research, sales, design, engineering, QA, security and delivery agents that take a client brief from discovery to deployment. Every irreversible step waits for a human signature.

Designed and built by the AlgoProfessor research lab. See all products at products.algoprofessor.com and the main website at www.algoprofessor.com.

12 specialist agents 1 human CEO with veto 5-stage Plan · Retrieve · Reason · Act · Evaluate loop 100% actions logged to audit ledger
algocrew://mission-control idle · pick a mission
Growth
Delivery
Trust & Ops
Mission timeline · agent-hoursGrowthDeliveryTrust
0Tasks done
0/12Agents used
0Agent-hours
D0 09:00Sim clock
SU
SUTRAChief of Staff · waiting for a brief
Tap any agent in the chart to see what it does, or run a mission.
Growth 0%
Delivery 0%
Trust & Ops 0%
> mission queue emptyChoose a sample mission or type a client brief, then press Run mission. What you will see:
  1. SUTRA splits the brief into workstreams
  2. Research, design, engineering and QA agents work in turn
  3. Security and ethics checks run before anything ships
  4. Deploys and client messages wait for your approval
  5. A mission report with hours, tests and decisions

Simulation for illustration. Figures are modelled per mission type, not measured client results.

The Crew

Twelve agents, three divisions, one reporting line.

Each agent owns a function a software firm already has. They share one memory, one tool registry and one audit ledger, so work hands off cleanly instead of being copy-pasted between apps.

Portfolio · Built by the crew

Seven AlgoProfessor products, shipped on the same agent core.

The products below run on the AlgoAgentic stack that powers AlgoCrew OS. Two are live; the rest are delivered as enterprise pilots scoped to client data.

How it works

Every task runs the same five-stage loop.

SUTRA wraps each delegated task in this loop. If Evaluate fails, the task goes back to Plan with the failure attached, up to three times, then escalates to a human.

Stage 1

Plan

SUTRA decomposes the brief into workstreams, assigns owners and sets acceptance criteria.

Stage 2

Retrieve

Agents pull from the shared GraphRAG memory: past proposals, code, client notes and research.

Stage 3

Reason

Chain-of-thought planning with tool selection over MCP: repos, CRM, calendars, CI and cloud.

Stage 4

Act

Reversible actions run directly. Deploys, payments and outbound messages queue for approval.

Stage 5

Evaluate

PARIKSHA and DHARMA score the output against tests, policy and the original acceptance criteria.

Stack:LangGraphCrewAIAutoGenMCPGraphRAGMLflowKubernetes
Governance · DHARMA layer

Autonomous where it is safe. Accountable everywhere.

An AI workforce is only useful if a client, an auditor and your own board can see why it did what it did.

Human approval gates
Production deploys, contracts, pricing, payments and any message to a new external contact need a named human to approve.
Full audit ledger
Every prompt, tool call, input and output is written to an append-only ledger with the agent, model version and timestamp.
Least privilege
Each agent gets only the tools and data scopes its role needs. KAVACH reviews scope changes.
Data protection
PII masking before model calls, India data residency option, DPDP Act 2023 and GDPR aligned retention.
Bias and fairness checks
DHARMA tests outreach, screening and scoring outputs for skew across protected attributes before release.
Kill switch
One click pauses all agents mid-loop. Work in progress is saved, nothing half-finished is pushed.
audit-ledger · sample entries
10:41:07NIRMANgit.push branch=feat/appointments tests=186/186
10:41:52KAVACHsast.scan critical=0 medium=2 → patched
10:42:30DHARMApolicy.check data=PHI mask=on residency=IN ✓
10:43:11YANTRAdeploy.request env=prod → HELD for approval
10:47:02CEOapprove deploy.request id=dr-0193 signer=human
10:47:40YANTRAdeploy.prod ok rollback=ready

Approval matrix

Research, drafts, designs, internal notesAgent runs
Code to a pull request, tests, staging deploysAgent runs
Production deployHuman signs
Pricing, contracts, proposals sent outHuman signs
First message to a new contactHuman signs
Payments and refundsHuman signs
DPDP Act 2023GDPRISO 27001 controlsOWASP Top 10SEBI audit trailRBI outsourcing
Engagement models

Start with one workflow. Scale to the whole crew.

4-week pilot

Crew Pilot

  • 3 agents on one workflow you choose
  • Your data, your cloud or ours
  • Weekly review with AlgoProfessor research team
  • Go / no-go report with measured results
Enquire
Quarterly

Crew Team

  • All 12 agents across Growth, Delivery, Trust & Ops
  • Integrations with your repos, CRM, mail and calendars
  • Custom approval matrix and audit ledger
  • Dedicated forward-deployed engineer
Enquire
Annual

Crew Enterprise

  • Private deployment, on-prem or VPC
  • Custom agents trained on your playbooks
  • Compliance pack: DPDP, ISO 27001 mapping
  • Co-published research and patent track
Enquire
Frequently asked questions

AlgoCrew OS, answered.

What is AlgoCrew OS?

AlgoCrew OS is an agentic AI workflow platform from AlgoProfessor AI R&D Solutions. It gives a software company a team of twelve AI agents, led by an orchestrator agent called SUTRA, that research, sell, design, build, test, secure and deliver client projects under human approval.

Who is it built for?

IT services firms, product studios, startups and university technology cells that deliver software projects for clients and want faster proposals, delivery and QA without losing control of what ships.

Do the agents act without human approval?

No. Research, drafts, code in pull requests and staging deploys run automatically. Production deploys, pricing, contracts, payments and first contact with new people always wait for a named human to approve.

Where is client data stored?

On your cloud, on-premises or in AlgoProfessor-managed infrastructure with an India data-residency option. PII is masked before model calls, and handling is aligned with the DPDP Act 2023 and GDPR.

Which tools and frameworks does it use?

The agent layer is built with LangGraph, CrewAI, AutoGen and the Model Context Protocol (MCP), with GraphRAG memory, MLflow and Kubernetes. It connects to your repositories, CRM, mail, calendars and CI/CD.

How do we start?

Most teams begin with a 4-week Crew Pilot on one workflow. Send an enquiry from this page or write to cto@algoprofessor.com. More about AlgoProfessor is at www.algoprofessor.com.

Enquiry desk

Put the crew on your next client project.

Tell us what your firm builds and where delivery slows down. Enquiries go straight to our CTO office, and we reply within one business day.

CTO office · enquiriescto@algoprofessor.com
CEO officeceo@algoprofessor.com
Phone / WhatsApp+91 63034 32833
LocationHyderabad, Telangana, India
  1. Reply within one business day from the CTO office with a few questions about your stack.
  2. 30-minute live demo of the crew running a mission on an example from your industry.
  3. Pilot scope: one workflow, success metrics and the approval matrix, agreed in writing.
  4. Week-1 kickoff with a forward-deployed engineer in Hyderabad or remote.
Delivered to cto@algoprofessor.com