Domain services modeled to your business. AI agents embedded in every workflow. Evaluation loops that gate every release. Human-in-the-loop for anything with commercial consequence. This is not AI bolted onto a legacy system. This is the operating model.
An AIOS build produces a production AI platform where structured data, agent intelligence, guardrails, and evaluation loops are baked into the architecture from day one.
Bounded modules that own your business objects. Leads, profiles, contracts, invoicing, notifications. Each publishes events to one stream. Every object has one source of truth.
Agents with defined triggers, tool sets, JSON output contracts, and human-in-the-loop policies. Email triage, lead assignment, matching, contract drafting, finance reconciliation, copilot.
One control plane across all agents. PII redaction on outbound LLM calls. Confidence thresholds. Cost caps per workflow. Provider fallback with automatic failover. Prompt versioning with rollback.
For every agent, the evaluation harness is built before the agent, from your historical data, during discovery. Release gates enforce acceptance criteria in CI. No agent ships without passing its own test suite.
Bounded domain modules with explicit event contracts, deployed as one service over consolidated PostgreSQL and one event stream. Module boundaries enforced in code. Any module can split later without redesign.
| Domain Service | Owns | Phase |
|---|---|---|
| Lead & Assignment | Lead, Assignment routing | 1 |
| Entity Profile & Media | Profiles, media assets | 1 |
| Search & Recommendation | Indexes, scoring, ranked results | 2 |
| Package & Booking | Projects, packages, bookings | 2 |
| Contracts & eSign | Contract lifecycle, signatures | 3 |
| Finance & Invoicing | Invoices, payments, payouts | 3 |
| Notifications | Templates, delivery, threads | 1+ |
| Admin & Configuration | Users, roles, config | 0/1 |
| Analytics & Reporting | Metrics, dashboards | 5 |
Domain services are illustrative, drawn from a reference engagement. Every AIOS build is scoped to the client's actual business objects through Production Discovery.
Every AIOS build follows these architectural commitments. They are not negotiable, because they are what make the AI capabilities achievable and maintainable.
Per business object. No duplicate masters, no reconciliation jobs, no conflicting records.
Confidence-flagged extraction. Free-text becomes structured on ingestion, not after the fact.
Users encounter AI in their existing screens and workflows. Not a separate chatbot tab.
For anything with commercial consequence. AI drafts. Humans commit. Always.
Harnesses built before agents. Release gates in CI. No agent reaches production without passing its own test suite.
Every state change, every AI action, platform-level. Append-only, object-locked, 7-year retention.
The AIOS build follows the same modular methodology as every Faction engagement. The scope is larger. The methodology is identical. Three demos per module. Working software, not slide reviews.
13-layer scan of your current systems, data, and workflows. Scorecard, modular scope, and a Statement of Work ready to sign.
Identity, data model, event stream, audit log, CI/CD, evaluation harness scaffolding, migrate-or-freeze triage. The substrate everything runs on.
Domain services and agents built in parallel tracks. Three demo checkpoints per module. Each phase closes on written exit criteria. Stop at any gate.
Agent quality monitoring, prompt tuning, security patches, feature iteration across web and mobile. Your platform keeps getting better.
AIOS builds are scoped during Production Discovery. Typical platforms run 25-50 modules over 28-32 weeks. Fixed quote and timeline before any build work starts. You can stop at any phase gate.
Typical AIOS scope: 25-50 modules ($200K-$400K), 28-32 weeks. Must-tier launch possible at 40 modules / 28 weeks. Payment gates at each phase; stop anytime with working, documented, usable software.
Every product is standalone. Every product connects. AIOS is where they come together as one platform.
13-layer scan. The discovery becomes the AIOS build plan.
Managed finishing pipeline. Your Git, our engineering, production on a cadence.
Self-hosted AI inference, database, monitoring. You own the infrastructure.
Production monitoring across every deployed agent and service.
Merge legacy repositories, upgrade frameworks, layer AI in "later phases." Preserves existing technical debt. Treats AI as an add-on. 12-18 months before any intelligence reaches production.
Greenfield AI-native. AI agents embedded in every workflow from day one. Structured data by default. Evaluation loops gate every release. Agents earn production access through their own test suites. Intelligence ships in Phase 1.
Production Discovery scans your systems, scores them across 13 layers, and produces a modular build plan with a Statement of Work ready to sign. 24 hours. $200. No commitment beyond that.
Start Production DiscoveryAIOS builds run on the same methodology that powers every Faction engagement: the Conveyor Belt pipeline, $8K modular delivery, and three demo checkpoints per module.