AI That Ships Production Code
The End of AI Slop
A fully autonomous SDLC with 22 quality analyzers, 15 security scanners, adversarial review, mutation testing, and cryptographic attestation on every release.
A fully autonomous SDLC with 22 quality analyzers, 15 security scanners, adversarial review, mutation testing, and cryptographic attestation on every release.
Nineteen integrated domains that cover every phase from requirements to deployment — with quality gates at every handoff.
38 specialized agents route every task through the right expertise. 5-signal classification determines complexity, and tiered quality gates ensure nothing moves forward without review.
Extensible at every level. 9 lifecycle hooks intercept every tool call, every session start, every context compression. Skills, commands, and MCP integration let you customize the entire pipeline.
Trust levels, data classification ceilings, audit trails, and LLM threat detection. Every agent action is logged, every permission is enforced, every decision is traceable.
Agents learn from every interaction. 69 MCP tools, Qdrant vector store, Memgraph knowledge graph with temporal edges, stigmergy coordination, 32 n8n consolidation workflows. Procedures, trajectories, and learnings accumulate into organizational intelligence.
Hierarchical context ensures agents maintain coherent behavior across sessions, projects, and teams. Auto-memory and intelligent compression prevent context loss.
D3.js knowledge graphs, semantic search, drift detection, and collection monitoring. See what your agents know, what they've learned, and where knowledge gaps exist.
Clean, token-efficient content from any URL. Agents consume documentation, APIs, and reference material without wasting context on HTML noise.
End-to-end data lineage, quality validation, pipeline observability, continuous PII classification, and financial reconciliation with calculation replay. Trace any output back to its source, prove mathematical integrity across system boundaries. Its source. Built for insurance regulatory requirements.
37 integrated tools across 6 quality pillars. 12 scan profiles from 30-second pre-commit to full audit. A 6-stage enrichment pipeline eliminates 95% of false positives. Cryptographic attestation with Ed25519 signatures.
Per-interaction cost tracking, four-tier budget hierarchy (org/project/agent_class/agent_instance), semantic caching, prompt cache tracking, intelligent model routing (Haiku/Sonnet/Opus), and Cost Per Successful Outcome (CPSO) metric. Know what every agent costs, set limits, and maximize ROI.
Behavioral anomaly detection, identity lifecycle management, memory integrity verification, and inter-agent collusion scoring. Gartner-aligned guardian agent oversight.
Automated failure recovery with pattern-based classification, YAML strategy playbook, checkpoint-aware restart, and model tier downgrade. Fail open — recovery never masks real errors.
Centralized event taxonomy with YAML routing rules, n8n workflow registry, dead letter queue with replay, and SLA-tracked workflow health monitoring across all 15 automation workflows.
Structured business rules, decision trees, SOPs, and edge-case catalogs. Agents query domain knowledge at decision points through MCP tools with full provenance tracking.
Beyond cost tracking — task completion rates, time-to-resolution, first-pass success, rework frequency, and ROI attribution. Passive observation of existing system events, no new instrumentation.
Historical workload analysis drives adaptive model routing, cache pre-warming, cost forecasting with confidence intervals, and concurrency optimization. Statistical, not ML.
External agent gateway with REST, MCP Bridge, and Google A2A protocol adapters. 15 of 38 agents exposed via Agent Cards at /.well-known/agent.json with tiered authentication, rate limiting, and governance-aware context sharing.
Human attribution, cryptographically-chained immutable audit events, signed evidence packages, data subject rights router, model cards, incident response with 72-hour clock. Audit-ready coverage for NAIC, SOX, GDPR/EU AI Act, NY DFS Part 500, SOC 2, ISO 27001, and GLBA.
Web portal for compliance officers, auditors, data subjects, and domain experts. Audit explorer, evidence packages, gate decisions, DSR management, model cards, regulatory reports. The missing surface that makes PRD 18 operable.
Code quality and security are different problems. We attack both with dedicated tool chains that work together through a unified enrichment pipeline.
Raw tool output is noise. Other platforms dump thousands of unranked findings on your desk. Our pipeline transforms that chaos into a ranked, actionable set — eliminating the false positives that make developers ignore security tools.
Every codebase gets a comparable, quantitative quality number. The sqrt penalty curve means your first critical finding hurts the most — no hiding behind "good enough."
Don't trust — verify. Every scan result is Ed25519-signed with Rekor transparency log entries. SLSA Level 3 provenance proves what was scanned, when, and what was found.
Tests that pass aren't enough. Mutation testing injects real bugs into your code and verifies your test suite catches them. Stryker (JS/TS), mutmut (Python), Pitest (Java). If your tests can't detect a mutant, they can't detect a real bug.
One AI writes the code. A different AI tries to break it. The critic agent runs independently with a mandate to find every weakness, every edge case, every assumption that could fail in production. Nothing ships without surviving adversarial review.
The reason most AI-generated code is untrusted: there's no paper trail. BulletproofSoftware.ai produces auditable documentation at every phase — so humans can review, approve, and verify without reading every line of code.
Automatically extracted from natural language input. Structured requirements with acceptance criteria, priority, and traceability IDs that carry through the entire pipeline.
Every design choice documented with context, options considered, rationale, and consequences. Your future self (and your auditors) will thank you.
Real-time quality scoring as code is written. Every scan result, every finding, every suppression decision is documented with rationale — not just a pass/fail.
The critic agent's full review: what was tested, what was found, what was fixed, and what was accepted. Includes mutation testing results and adversarial review findings.
Tamper-proof evidence that this code was scanned, reviewed, and approved. Verifiable by anyone with the attestation ID — no trust required.
15 structured event types streamed to your SIEM. Every agent action, every tool call, every data access, every policy decision — forensic-grade and queryable.
Ed25519-signed bundles produced on demand for any session. Session record, cryptographically-chained audit trail, gate decisions, model cards, and lineage — in one auditor-ready package. 7-year retention. NAIC / SOX / GDPR / NY DFS / SOC 2 / ISO 27001 / GLBA.
Six phases. Six gates. 24+ document types generated automatically. Every gate requires documented evidence before the next phase begins. The teal tags below show what each phase produces — these are the artifacts your reviewers sign off on.
Not paperwork. Runtime enforcement. Every agent operates within its declared trust boundary, and every violation is logged.
Every agent declares its trust level (1–5), permitted tools, and data classification ceiling. No agent can exceed its manifest.
Four tiers: public, internal, confidential, restricted. Ceiling enforcement prevents agents from accessing data above their clearance. Restricted = hard stop, no override.
Tools are classified as exempt, standard, or elevated. The policy engine evaluates every tool call against agent trust level, task tier, and data classification in real time.
Real-time monitoring for prompt injection, encoding attacks, system prompt leakage, jailbreak attempts, and PII exposure across all agent interactions.
Every MCP tool call passes through DLP screening. Content classification gates prevent data exfiltration through external integrations. Nothing leaves without inspection.
Define behaviors that trigger immediate termination. Configurable per agent, per trust level. No warnings, no retries — hard stop.
15 structured audit event types streamed to Wazuh or any SIEM. Forensic-grade payloads for incident response, compliance audits, and regulatory reporting.
Non-human identity lifecycle management with per-invocation forensic chains. Cost tracking prevents denial-of-wallet attacks. Every agent session is accountable.
Every session anchored to an authenticated human identity with MFA verification, lawful basis, and named responsible person (NAIC). All agent actions inherit the human user as a foreign key.
Cryptographically-chained audit events with SHA-256 prev-hash and sequence numbers. Tamper-evident and reorder-proof. Replaces SQLite WAL with append-only PostgreSQL. 7-year retention floor.
GDPR Articles 15-22 with 30-day SLA tracking. Erasure cascades across Qdrant, Postgres, n8n, and vector memory. Every deletion itself logged. Automated decision objections pause processing.
Four-tier cost governance: organization → project → agent class → agent instance. Warn / throttle / pause thresholds per level. CPSO (Cost Per Successful Outcome) links spend to value delivered.
From requirements to production — with proof at every step.
Other platforms use "autonomous" to mean "unsupervised." We use it to mean "self-governing." Every step has checks. Every output has attestation. Every decision has an audit trail.
The result: code you can actually deploy to production without wondering what the AI got wrong.
// What happens when you give BulletproofSoftware.ai a task:
REQUIRE → BRD extracted, threats mapped
GATE ← requirements approved
DESIGN → architecture reviewed, agents routed
GATE ← design approved
BUILD → 38 agents, real-time scanning
GATE ← quality score ≥ threshold
VERIFY → 37-tool scan, mutation testing
GATE ← critic agent approved
ATTEST → Ed25519 signed, SLSA provenance
GATE ← attestation verified
SHIP → deploy with full audit trail
// Compare to everyone else:
PROMPT → CODE → HOPE → SHIP22 code quality analyzers. 15 security scanners. 6-stage enrichment. Mutation testing. Adversarial review. Cryptographic attestation. This is what production-grade AI development looks like.