350+
Active practitioners
8
Talent tracks
2-week
Placement SLA
4
Countries
25+
Unicorns served
94%
12-month retention
72-hour
QIA shortlist
400+
Pre-vetted engineers
11 days
Average placement
We fill AI roles using AI. Meet QIA.
QIA (Qapitol Intelligence Agent) automates talent fulfillment, parsing requirements, matching candidates, and shortlisting within 72 hours rather than two weeks. Current bench: 40+ pre-vetted AI/ML engineers available now; average placement: 11 days; 5-day shortlist guarantee.
- Step 1 · Brief received: QIA parses role requirements, seniority, stack, timeline automatically
- Step 2 · Bench match + outreach: QIA matches against 400+ profiles and initiates simultaneous outreach
- Step 3 · AI screening (72 hrs): Automated technical screen + human validation; 3-5 candidates delivered
- Step 4 · Your interviews → Placed: Client interviews and selects; Qapitol handles onboarding (typically 14 days)
Why Qapitol Talent: The difference between a staffing firm and an execution partner
Comparison of traditional staffing vs. Qapitol Talent.
- Screening: CV matching only (traditional) vs. deep technical + domain assessment (Qapitol)
- Skills Training: generic (traditional) vs. platform-trained on QAVE, CHEQ, Agent Fabric, Nexus (Qapitol)
- Accountability: timesheet-based (traditional) vs. outcome-driven with milestones (Qapitol)
- Disciplines: QE or dev only (traditional) vs. 8 full-spectrum tracks (Qapitol)
- Methodology: reinvented per engagement (traditional) vs. SURE-Q certified framework (Qapitol)
- Geographic Coverage: India-only (traditional) vs. 4 countries: India, US, UK, Singapore (Qapitol)
- Onboarding: client responsibility (traditional) vs. 2-week productive deployment SLA (Qapitol)
Eight Talent Tracks
Full-spectrum talent tracks covering the AI delivery lifecycle.
- AI & ML Engineering: Build and deploy production AI. From LLM fine-tuning to ML pipelines to Gen AI product development. Roles: LLM Engineers, ML Engineers, AI Researchers, Gen AI Specialists, Prompt Engineers, Fine-tuning Specialists
- Quality Engineering: Test, validate, and assure across the full software and AI delivery stack. From API to AI output. Roles: QE Architects, SDET Automation Engineers, Performance Engineers, Security Testers, Accessibility Engineers
- MLOps & Data: Operationalise AI at scale. Build and run the data and model infrastructure that keeps AI in production. Roles: MLOps Engineers, Data Engineers, Data Scientists, Feature Engineers, Synthetic Data Specialists
- AI Governance & Compliance: Govern AI safely and defensibly. From internal AI audits to EU AI Act readiness to ongoing compliance monitoring. Roles: AI Auditors, Compliance Analysts, Risk Engineers, CHEQ Practitioners, EU AI Act Specialists
- Intelligent Automation: Automate what's repetitive, orchestrate what's complex. RPA to agentic workflows. Roles: RPA Developers, Agentic AI Builders, Workflow Automation Engineers, NLP Engineers
- AIOps & Reliability: Keep AI in production at enterprise scale. SRE, observability, and intelligent ops combined. Roles: AIOps Engineers, SREs, Observability Engineers, Incident Response Specialists
- Forward Deployment: Senior Qapitol practitioners embedded at your site to lead and deliver AI transformation. Not advisory. Execution. Roles: AI Transformation Leads, Embedded Engineering Managers, Principal AI Engineers, Outcome Delivery Managers
- Product & Domain: Bridge AI capability and business impact. Domain SMEs who understand your sector and can translate between engineering and outcomes. Roles: AI Product Managers, Business Analysts, BFSI Domain SMEs, Healthcare Domain SMEs, Retail/Logistics SMEs
Engagement Models
Four engagement models for deploying Qapitol talent.
- Staff Augmentation (Most Common): Individual practitioners placed within your team. They operate under your management, within your tools and processes, but arrive platform-trained and SURE-Q certified. 2-week placement SLA, guaranteed; all 8 tracks available; flexible duration (sprint to multi-year); Qapitol manages ramp-up; monthly outcome reporting.
- Embedded Squads (High Impact): Full cross-functional teams deployed directly into your environment. AI Engineering + MLOps + QE + AIOps in one squad, working as a unified delivery unit. Pre-assembled, pre-aligned squad; typically 4-12 practitioners; single point of accountability; quarterly expansion/reconfiguration; platform stack deployed in client environment.
- GCC Capability Build (GCC Specialist): Dedicated talent, platforms, and governance infrastructure for Global Capability Centres in India. End-to-end GCC setup in 90 days (Launchpad); platform deployment included; SURE-Q governance from day one; knowledge transfer and handoff plan.
- Forward Deployment (Senior Practitioners): Senior Qapitol practitioners placed onsite to lead and deliver AI transformation. This is not advisory. They own outcomes, lead delivery, and leave behind institutional capability. Minimum 3-month engagement; practitioner-level expertise; owns defined transformation deliverable; available in India, US, UK, Singapore; transition plan built-in.
Pre-Deployment Certifications
All practitioners are certified before deployment.
- QAVE Trained, Practitioners are trained on the QAVE AI Simulation and Evaluation Engine before deployment, running eval pipelines from day one.
- CHEQ Certified, AI Governance and Compliance practitioners hold CHEQ platform certification, able to configure AI compliance workflows, audit pipelines, and regulatory reporting from week one.
- Agent Fabric Ready: Automation and AI Engineering practitioners are trained on Agent Fabric (Qapitol's autonomous execution framework) and can deploy agentic workflows immediately.
- Domain Assessed: Practitioners placed in BFSI, Healthcare, Retail, Logistics, or Tech programmes complete domain assessment prior to placement.
Track Record
Client testimonials from talent engagements.
- Nishant Rao (NR), Head of Engineering, Leading NBFC, India GCC Build: "We needed 12 AI Engineers and 4 MLOps practitioners for our GCC build in 6 weeks. Every other firm quoted 3 months. Qapitol placed 14 of 16 in 5 weeks: all platform-trained, all domain-assessed for NBFC environments. The ramp time was essentially zero."
- Sneha Pillai (SP), VP Technology, D2C Unicorn, Embedded Squad Engagement: "The embedded QE + AIOps squad cut our release cycle by 40% in 10 weeks. Not 40% fewer bugs. 40% faster releases. They owned outcomes: weekly delivery reports, defined SLAs, escalation paths. It felt like a delivery partner, not a vendor relationship."
- Aarav Verma (AV), CTO, InsurTech, Forward Deployment Engagement: "We placed a Forward Deployment team to deliver an AI underwriting POC in 8 weeks. They didn't just recommend: they built, integrated, and handed over a production-ready model with full CHEQ governance instrumentation. That's what execution looks like."
Industry-Specific Offerings
Domain-assessed practitioners by industry.
- Banking & Financial Services (Risk models, NBFC lending, payment infrastructure, regulatory compliance, anti-fraud AI) domain-assessed practitioners only.
- Healthcare & Life Sciences (Clinical AI validation, HL7/FHIR systems, diagnostic model assurance, HIPAA-aware delivery) practitioners who understand the compliance landscape.
- Logistics & Supply Chain (Route optimisation, demand forecasting, real-time tracking, warehouse automation) practitioners who've shipped in logistics production.
- Retail & E-commerce (Recommendation engines, pricing AI, D2C platform assurance, personalisation infrastructure) practitioners who've delivered at unicorn scale.
- Tech & SaaS (LLM product development, AI feature assurance, MLOps at SaaS scale, agentic product delivery) practitioners who ship AI as product, not project.
Talent Transformation Resources
Three free resources for talent transformation.
- AI Fungibility Framework, Free Download, 90-Day Transformation Playbook: A practical, role-by-role guide to assessing AI readiness, mapping learning paths, and converting QA engineers, developers, and IT staff into AI-capable practitioners. Includes AI Readiness Scorecard (self-assessed), 90-day curriculum by role (QA, Dev, Ops), tool & platform recommendations, fungibility cost model (Excel). Format: PDF + Excel · Free · Requires email.
- Upcoming Webinar, From Traditional QA to AI-Native QE, A 90-Day Transformation Playbook. Free · 60 minutes · Recording available. Agenda: Why 70% of QE teams have the raw material to go AI-native; the 5 fungibility archetypes (and which describes your team); live walkthrough of the 90-day curriculum; Q&A with Qapitol's talent transformation leads.
- Free AI Skills Gap Analysis: For your engineering team. Process: submit your team profile (30-min form); Qapitol analysts map your team to AI archetypes; receive scored report + reskilling roadmap in 48hrs. Free · No obligation · 48hr turnaround.
Pricing Model Clarity
Three commercial models.
- Contingency (No Upfront Cost): No upfront cost. You only pay a placement fee when a candidate successfully joins: no success, no fee. Fee on successful placement only; 12-week guarantee with free replacement; no retainer, no minimum commitment. Best for: permanent hires, up to 3 simultaneous roles.
- Retained Search (Dedicated Partner): A dedicated talent partner works exclusively on your brief. Dedicated talent partner assigned; priority access to the full bench; weekly pipeline reports. Best for: urgent, specialist, or multiple simultaneous hires.
- RPO, Recruitment Process Outsourcing (Ongoing Supply), Qapitol runs your entire AI/ML hiring function end-to-end on a monthly retainer. Monthly retainer model; ongoing talent supply: no per-hire fees; GCC buildout support included. Best for: GCC buildouts or sustained hiring (10+ roles/year).
Ready when you are
Tell us what you're building. We'll field the right team. Describe your programme: the technology, the domain, the timeline, the expected headcount. A Qapitol talent director will respond within 24 hours with a matched practitioner profile and engagement recommendation. 350+ practitioners across 8 tracks · 2-week placement SLA · 4 countries · Outcome-accountable from day one.