Enterprise AI · Production MLOps · Agentic Systems
We design, fine-tune and operate large language models, multi-agent workflows and real-time decision engines on infrastructure your security team already trusts.
Methodology
Most enterprise AI programs stall between a promising notebook and a dependable service. The PTForce AI framework is a six-stage operating model that turns isolated experiments into governed, observable and cost-efficient automation. Each stage has explicit entry criteria, artifacts and owners, so engineering, risk and business leadership share a single definition of done.
We map every decision point in a business process, quantify latency, error cost and data availability, and rank automation candidates by measurable return rather than novelty. Output: a scored opportunity backlog tied to KPIs owned by an executive sponsor.
Feature stores, lineage-tracked lakehouse tables and governed vector indexes are provisioned before a single model is trained. Schema contracts and PII classification run in CI so downstream models never consume unvetted data.
Baselines first, then fine-tuned foundation models, LoRA adapters or classical gradient-boosted ensembles — whichever wins on a held-out evaluation harness that reflects real production traffic, cost and latency budgets.
Deterministic workflows wrap probabilistic models. Tool-calling agents operate inside typed state machines with guardrails, retries, human approval gates and full trace replay for audit and debugging.
Triton and vLLM endpoints on autoscaling Kubernetes node pools, continuous batching, speculative decoding and quantization profiles chosen per workload to hit p95 latency SLOs at the lowest GPU-hour cost.
Drift detectors, shadow deployments, canary releases and automated retraining triggers close the loop. Every model version ships with a model card, evaluation report and rollback plan.
Technology
We are framework-pragmatic, not framework-loyal. The stack below reflects what consistently survives contact with production traffic, security review and on-call rotations. Hover any tile to see where it fits in our reference architecture.
Research to production training with FSDP and torch.compile.
Legacy estimator migration and TF Serving interoperability.
Multi-framework inference server with dynamic batching.
PagedAttention LLM serving with continuous batching.
Composable retrieval and tool-use pipelines.
Distributed training, tuning and batch inference.
GPU scheduling, autoscaling and multi-tenant isolation.
Kernel-fused, quantized inference on NVIDIA hardware.
Governance
Generative models expand the attack surface: prompt injection, data exfiltration through retrieval, and over-privileged agents are now board-level risks. PTForce AI embeds controls at the platform layer so that every model, prompt and agent inherits the same guarantees by default, instead of relying on per-project diligence.
Change management, access reviews and evidence collection mapped to SOC 2 trust service criteria across every pipeline.
Customer-managed keys, private networking and region-pinned storage. Training data never leaves your tenancy.
Every prediction traceable to model version, prompt template, retrieved documents and input feature snapshot.
Adversarial prompt suites, jailbreak testing, toxicity and hallucination scoring before and after each release.
Bias and fairness analysis across protected attributes, documented in model cards aligned to NIST AI RMF.
Agents operate with scoped, short-lived credentials and explicit tool allow-lists; destructive actions require human approval.
The result is an AI estate that auditors can inspect, finance can forecast and engineers can operate at 3 a.m. without guesswork. Whether you are consolidating a sprawl of proofs-of-concept or launching your first customer-facing LLM feature, PTForce AI provides the architecture, delivery discipline and operational tooling to move from pilot to measurable production impact in weeks, not quarters.
Work directly with PTForce AI architects on model selection, serving topology and governance controls.