AI Services Portfolio

Five disciplines. One production standard.

PTForce AI services are delivered by cross-functional pods of ML engineers, platform engineers and applied researchers. Each engagement begins with a measurable objective and ends with a system your team can own, operate and extend. Whether you need a single fine-tuned model or an end-to-end agentic platform, the same engineering rigor applies.

SERVICE 01

Enterprise Large Language Models & Fine-Tuning

Foundation models are generalists; your business is not. We adapt open-weight and commercial LLMs to your terminology, documents and decision patterns while keeping data inside your security boundary.

Custom domain adaptation through continued pre-training on curated corpora
LoRA and QLoRA fine-tuning for cost-efficient, swappable task adapters
Retrieval-augmented generation with hybrid BM25 + dense vector search and cross-encoder re-ranking
Citation-grounded answers with hallucination and faithfulness scoring

SERVICE 02

Autonomous Agentic Workflows & Multi-Agent Systems

Agents become valuable when they are predictable. We build orchestrated agent systems where planning, execution and verification are separate, observable roles operating under explicit policies.

Orchestrated agent loops with supervisor, worker and critic roles
Typed tool calling against internal APIs with schema validation
Short-term scratchpads and long-term episodic memory stores
Deterministic evaluation layers, replayable traces and human approval gates

SERVICE 03

Production MLOps & Model Serving Infrastructure

The model is often the smallest part of an ML system. We engineer the platform around it so releases are routine, costs are predictable and regressions are caught automatically.

Kubernetes model orchestration with GPU-aware scheduling and node pools
Autoscaling Triton and vLLM endpoints driven by queue depth and token throughput
Automated data and concept drift detection with alerting
Continuous training (CT) loops with gated promotion and instant rollback

SERVICE 04

Computer Vision & Multimodal Intelligence

From factory floors to field operations, we deploy vision models that run where the pixels are — and fuse them with text, audio and sensor data for richer understanding.

Edge vision processing on Jetson and x86 accelerators with INT8 quantization
Real-time object detection, segmentation and tracking pipelines
Video telemetry analysis for safety, compliance and throughput metrics
Cross-modal embedding systems for image-text search and multimodal RAG

SERVICE 05

Predictive Modeling & Real-Time Decision Engines

When milliseconds matter, we pair proven statistical learning with streaming infrastructure to turn events into decisions before the opportunity — or the risk — passes.

Low-latency time-series forecasting with hierarchical reconciliation
Quantitative risk scoring with calibrated probabilities and explanations
Automated event triggers on Kafka and Flink streams
Online feature stores delivering sub-10ms feature retrieval

How engagements run

Every PTForce AI engagement follows a fixed cadence: a two-week discovery sprint produces an architecture decision record, risk register and evaluation plan; build sprints deliver working, deployed increments every two weeks; and a structured transition phase hands over runbooks, dashboards and on-call training. Pricing is tied to milestones, so you pay for shipped capability rather than hours.

We are cloud-agnostic and deploy into AWS, Azure, Google Cloud or air-gapped on-premise environments. Infrastructure is delivered as Terraform and Helm, models are stored in your registry, and no proprietary runtime is required to keep the system running after we leave.

Scope your production AI workload

Work directly with PTForce AI architects on model selection, serving topology and governance controls.

Request a technical consultation →