Pragmatic CTO
The challenge
AI initiatives stalling in POC limbo, unclear ROI, and governance questions blocking production.
What you need
A defensible path from codebase to production with partner engineers who own outcomes.
1Who we help
Built for teamsshipping AI to production.
Intronsoft agentic AI development fits teams that need production-grade AI grounded in real systems, not slide-deck strategy or disconnected POCs that never reach users.
Product leader
The challenge
Pressure to ship AI features while compliance, integration, and quality gates slow delivery.
What you need
Agentic workflows on your stack with architecture guardrails and audit-ready patterns from sprint one.
Head of data or AI
The challenge
Tribal knowledge in codebases, generic RAG that hallucinates, and no traceable lineage for auditors.
What you need
Codebase-grounded context, structured artifacts, and governance your board can trust.
We work across fintech, healthtech, SaaS, manufacturing, and other industries where AI must integrate with existing systems, data estates, and compliance requirements.
2What we deliver
From strategy to production,grounded in your systems.
Forward-deployed partner engineers on your stack, with delivery agents compressing codebase analysis, architecture, and governance design before sprint one.
AI strategy and use-case consulting
Prioritized use cases scoped to your data and compliance constraints.
Identify where AI creates measurable business value before you spend on build. Scoped to your data, systems, integration landscape, and compliance constraints.
Technology blueprint and architecture
Defensible architecture and integration plan before sprint one.
A defensible plan for what to build, how agents connect to your data and APIs, and how to govern outputs before a sprint begins.
Multi-agent system development
Production agentic workflows with orchestration and review gates.
Agentic systems that reason, plan, and execute inside your enterprise: orchestrated workflows with tool use, retrieval, and human review gates.
RAG and codebase-grounded context
Living documentation and agent-ready context from your codebase.
The Analyzer indexes your codebase into living documentation, dependency maps, and agent-ready context so agents answer from your estate, not generic training data.
Enterprise integration and tool use
Agents integrated with systems you already run.
Agents wired to your APIs, CRM, ERP, data platforms, and identity providers with clear contracts, versioning, and observability from sprint one.
MLOps, monitoring, and observability
Measurable AI performance with versioning and alerting in production.
Evaluation harnesses, prompt and model versioning, latency and cost tracking, and alerting so AI performance is measurable in production.
Governance, compliance, and human review
Audit-friendly artifacts and partner engineer sign-off.
SOC 2 Type II, ISO 27001, and HIPAA-aware patterns. Structured review gates, source citation, and partner engineer sign-off before artifacts reach users.
POC to production pathway
POC in weeks, production workflows in 60–90 days.
Working POC in 2–4 weeks, production agentic workflows in 60–90 days. Agent-compressed discovery replaces weeks of unstructured experimentation.
3Delivery agents · Analyzer & Architect
Grounded in your codebase,before the first sprint.
The Analyzer indexes your codebase into documentation agents can retrieve; the Architect defines agent architecture, data boundaries, and review gates. Context and governance land before your first POC sprint, not after a failed pilot.
Before sprint one
01
Analyzer
Living documentation, dependency maps, and agent-ready context.
Indexes your codebase into structured documentation, dependency maps, and context agents can retrieve, eliminating tribal knowledge risk before build begins.
02
Architect
Architecture options, integration patterns, and governance guardrails.
Produces agent architecture options, NFRs, data and API integration patterns, and governance guardrails: a defensible direction before production commitments.
Grounded context and defensible architecture come first, so POCs are not throwaway experiments. Partner engineers own evaluation design, model choices, and the path from demo to production.
Need full product delivery alongside AI features? See our custom software development service. Grounding agents in your data estate? Explore data and analytics.
4Engagement process
Phase by phase,with artifacts you keep.
You keep every artifact from the Codebase Context Scan forward. Partner engineers embed on your stack; the Analyzer and Architect run on your estate, not a reference architecture.
01
Codebase Context Scan
Free working session on your codebase and systems. Senior consultant runs Analyzer and Architect on your context.
You keep
Documentation sample, 2–3 use case ideas
02
Strategy and scope
Researcher intake, use-case prioritization, success criteria, data and integration requirements, compliance constraints.
You keep
Prioritized use-case backlog, risk register, delivery plan
03
Agent architecture and sprint zero
Architect finalizes agent design, retrieval strategy, API integrations, and guardrails. Planner prepares sprint one backlog.
You keep
Architecture decision record, NFRs, sprint-one backlog
04
Agile delivery and evaluation
Two-week sprints with embedded partner engineers. POC demos, evaluation metrics, and reprioritization each cycle.
You keep
Working agent increments, evaluation reports, test evidence
05
Production launch and governance
Deployment, monitoring, documentation, and knowledge transfer. MLOps runbooks and optional ongoing evolution.
You keep
Production agents, runbooks, governance artifacts, roadmap recommendations
Engineering pods typically deploy in 2–3 weeks after the Codebase Context Scan. POCs often reach first working demo in 2–4 weeks; production agentic workflows in 60–90 days depending on scope. We quote honestly after the working session, not from a generic rate card.
Quality gates and evaluation harnesses are supported by our AI-powered QA practice throughout delivery.
5Partner engineering
Human layer
Partner engineering makes it accountable
Our engineers embed inside your organization, domain-matched, senior, and outcome-aligned. Not a delivery center.
- Domain-matched to your stack and business
- Senior, they own architecture and production decisions
- Outcome-aligned, clear delivery and quality goals
99%
99% client renewal across multi-year engagements.
6Case study
Production outcomes.Partner engineering.
Embedded senior engineers who own results in production, drawn from 120+ delivered projects. 95% of new clients come from referrals.
7Next steps
Free working session
Every engagement starts here.
Book a call, run a session on your context, and receive a tailored proposal with no commitment required.
- 1
Schedule a call
At your convenience.
- 2
Working session
Senior consultant, not an SDR.
- 3
Tailored proposal
Yours to keep, either way.
7FAQ
AI strategy, use-case consulting, agent architecture, multi-agent development, RAG and codebase grounding, enterprise integrations, MLOps, governance, and optional ongoing support. The Analyzer and Architect ground agents in your codebase and produce defensible architecture before build; partner engineers own production launch and governance.
Generic consulting produces slide decks; we compress discovery with delivery agents and embed partner engineers who ship to production. The Analyzer grounds agents in your codebase; the Architect produces defensible architecture before build. POCs typically land in 2–4 weeks, not quarters of open-ended exploration.
Yes. The Analyzer indexes your codebase into living documentation and agent-ready context. Agents integrate with your APIs, data platforms, and identity providers with architecture guardrails documented before build.
Working POCs typically land in 2–4 weeks. Production agentic workflows in 60–90 days depending on scope, integration complexity, and compliance requirements. We quote honestly after the Codebase Context Scan.
SOC 2 Type II, ISO 27001, and HIPAA-aware patterns from sprint one. Structured review gates, source citation, evaluation harnesses, and partner engineer sign-off before agents reach users.
A documentation sample and 2–3 use case ideas from your codebase, run by a senior consultant using the Analyzer and Architect. You keep the artifacts. We respond within 24 hours with no commitment required.
Related services
Agentic AI engagements often extend into custom product delivery, data platform work, or quality automation. Explore what pairs with your roadmap.